TensorFlow Jobs

Data Scientist:We are seeking a highly skilled Data Scientist AI to design, develop, and deploy advanced machine learning and artificial intelligence solutions. The ideal candidate will work on large datasets, build predictive models, and collaborate cross-functionally to deliver scalable, data-driven products.Key ResponsibilitiesDesign, develop, and optimize machine learning and deep learning models.Work on AI/ML projects including NLP, computer vision, recommendation systems, and generative AI.Perform data cleaning, feature engineering, and exploratory data analysis (EDA).Build and manage data pipelines and model training workflows.Deploy models into production and monitor performance.Collaborate with Product, Engineering, and Business teams to translate business problems into AI solutions.Conduct model evaluation, A/B testing, and performance tuning.Document models, experiments, and technical processes.Required Skills & QualificationsClassic Machine learning (Regression, predictive Analysis, Classification, Clustering)Machine learning Model OptimisationStrong proficiency in Python (NumPy, Pandas, Scikit-learn).Hands-on experience with Deep Learning frameworks: TensorFlow, PyTorch, or Keras.Experience in Natural Language Processing (NLP) and/or Computer Vision.Strong knowledge of Machine Learning algorithms and statistics.Experience with SQL/NoSQL databases and big data tools (Spark, Hadoop preferred).Experience with MLOps tools such as Docker, Kubernetes, CI/CD pipelines.Preferred SkillsExperience with LLMs / Generative AI (OpenAI, Hugging Face, LangChain).Cloud experience (AWS, Azure, or GCP).Experience building AI APIs and microservices.EducationBachelors or Masters degree in Computer Science, Data Science, AI, or a related field. (PhD preferred for advanced research roles)Soft SkillsStrong problem-solving and analytical thinkingExcellent communication and storytelling skillsAbility to work in fast-paced, cross-functional teamsTPBN1_UKTJ

Data Scientist

InfinityQuest Ltd,

Glasgow

Data Scientist:We are seeking a highly skilled Data Scientist AI to design, develop, and deploy advanced machine learning and artificial intelligence solutions. The ideal candidate will work on large datasets, build predictive models, and collaborate cross-functionally to deliver scalable, data-driven products.Key ResponsibilitiesDesign, develop, and optimize machine learning and deep learning models.Work on AI/ML projects including NLP, computer vision, recommendation systems, and generative AI.Perform data cleaning, feature engineering, and exploratory data analysis (EDA).Build and manage data pipelines and model training workflows.Deploy models into production and monitor performance.Collaborate with Product, Engineering, and Business teams to translate business problems into AI solutions.Conduct model evaluation, A/B testing, and performance tuning.Document models, experiments, and technical processes.Required Skills & QualificationsClassic Machine learning (Regression, predictive Analysis, Classification, Clustering)Machine learning Model OptimisationStrong proficiency in Python (NumPy, Pandas, Scikit-learn).Hands-on experience with Deep Learning frameworks: TensorFlow, PyTorch, or Keras.Experience in Natural Language Processing (NLP) and/or Computer Vision.Strong knowledge of Machine Learning algorithms and statistics.Experience with SQL/NoSQL databases and big data tools (Spark, Hadoop preferred).Experience with MLOps tools such as Docker, Kubernetes, CI/CD pipelines.Preferred SkillsExperience with LLMs / Generative AI (OpenAI, Hugging Face, LangChain).Cloud experience (AWS, Azure, or GCP).Experience building AI APIs and microservices.EducationBachelors or Masters degree in Computer Science, Data Science, AI, or a related field. (PhD preferred for advanced research roles)Soft SkillsStrong problem-solving and analytical thinkingExcellent communication and storytelling skillsAbility to work in fast-paced, cross-functional teams

Senior Data Scientist

Senior Data Scientist - Customer Data Salaries in the region of £70,000 - £85,000 DoE Hybrid working - 2/3 days central London office Job Reference J13015Full UK working rights required/no sponsorship availableImmediate requirement - strong leadership skillsWe are seeking for an experienced, passionate and highly motivated Data Scientist who will help discover the information hidden in vast amounts of customer data, and help make data driven decisions to deliver better products, service and relevance to the customers.Not specifically managing others, but management of your own workload, taking initiative to mould the role into your own and come with a pragmatic mindset.The role Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product embeddings and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle-from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback.SkillsProven experience in machine learning, particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with marketing, CRM, and engineering teams. Excellent communication and stakeholder management skills Experience in a global or multi-regional context is a plusIf you would like to hear more, please do get in touch.Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme.Datatech is one of the UK’s leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data. For more information, visit our website: www.datatech.org.uk

Senior Machine Learning Engineer

£55,000 - 65,000 GBPHybrid WORKINGLocation: Central London, Greater London - United Kingdom Type: PermanentSenior Machine Learning Engineer - National Security (London, Hybrid) Salary: Up to £65,000 per year + £7,000 DV clearance bonus (tax-free, subject to eligibility) Working Model: Hybrid - 3 days on client site once clearance is granted, 1 day in central office, remainder remoteA leading UK national security-focused technology organisation is seeking a Senior Machine Learning Engineer to join its AI team. You will design, develop, and deploy ML models and LLM/GenAI solutions to solve real-world national security challenges. This is a highly innovative, collaborative, and impactful environment where you will apply cutting-edge machine learning methods to unique datasets.Key responsibilities:

Lead and contribute to ML projects, including forecasting, classification, anomaly detection, and LLM/GenAI applications.

Design experiments, formulate hypotheses, evaluate results, and iterate rapidly to validate approaches.

Transition experimental models into production-ready solutions, collaborating with engineers on deployment, monitoring, and optimisation.

Build and maintain ML pipelines using AWS services and modern MLOps/LLMOps tooling.

Implement robust versioning, experiment tracking, and reproducibility practices.

Mentor junior engineers and contribute to team-wide AI knowledge sharing.

Communicate complex technical concepts to both technical and non-technical stakeholders.

Ideal candidate:

BSc, MSc, or PhD in a quantitative discipline (e.g., Maths, Physics, Computer Science).

4-5 years’ experience in ML/AI engineering or data science roles (senior level).

Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost).

Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC).

Proven track record transitioning models from experimentation to production with governance and quality controls.

Experience developing LLM/GenAI solutions and familiarity with LLMOps tools.

Strong problem-solving, communication, and project delivery skills.

Eligible for UK DV security clearance; candidates without clearance must be able to undergo the process.

Why this role is unique:

Work on national security projects with niche datasets unavailable elsewhere.

Influence AI adoption from the ground floor for high-profile government clients.

Join a collaborative team of over 4,000 digital, cyber, and intelligence specialists across multiple locations.

Hybrid working flexibility, generous benefits, career development support, and a culture valuing diversity and inclusion.

For further information, feel free to reach me at 02895213213, or simply apply!

AI/ML Architect

Stott & May Professional Search Limited

AI / ML Architect Location: London (Hybrid - 2 days/week onsite) Duration: 6 months Day Rate: £510 per day (Inside IR35) Role Overview We are seeking an experienced AI / ML Architect to design, build, and lead the deployment of advanced machine learning and AI-driven solutions. The successful consultant will enable real-world value from data by architecting models, pipelines, and integration patterns that scale across the organisation. This role combines technical depth, applied ML engineering, solution design, and hands-on development. Key Responsibilities

Design, build, and train end-to-end machine learning models across NLP, predictive analytics, classification, and computer vision use cases

Experiment with algorithms, optimise hyperparameters, and evaluate model performance

Collect, process, and prepare structured and unstructured datasets for model training and validation

Implement feature engineering, data augmentation, and data quality controls

Develop APIs, services, or microservices to integrate models into production platforms

Deploy, monitor, and manage models using MLOps tooling, automation, and versioning practices

Analyse performance metrics (accuracy, precision, recall, F1-score) and optimise models for scalability and efficiency

Collaborate with product teams, engineers, and data scientists to translate business requirements into technical solutions

Document architectures, workflows, and methodologies to ensure reproducibility and maintainability

Stay current on emerging AI technologies including generative models, reinforcement learning, and transformer-based architectures

Profile & Required Expertise

10+ years software engineering experience, including 5+ years in applied AI/ML

Advanced proficiency in Python, PyTorch, TensorFlow, and modern NLP frameworks

Hands-on experience with LLMs, transformer architectures, LangChain, and Hugging Face

Strong knowledge of algorithms, machine learning lifecycles, and model evaluation techniques

Deep understanding of BFSI environments including risk, compliance, and AML/KYC

Practical experience with cloud platforms (AWS/Azure/GCP) and containerisation (Docker/Kubernetes)

Experience building scalable ML systems and secure, production-grade applications

Proven ability to work collaboratively in cross-functional teams

Strong communication skills with the ability to present technical concepts to non-technical stakeholders

Demonstrated ability to write clear documentation and apply engineering best practices

Desirable Experience

Ability to align ML strategies with long-term business and platform objectives

Familiarity with emerging trends in generative AI, RAG workflows, or reinforcement learning

Experience influencing architecture decisions at enterprise scale

Data & AI Senior Consultants - Dynamic AI Consulting firm

Data & AI Senior ConsultantsLocation - We are flexible: onsite, hybrid or fully remote, depending on what works for you and the client, UK or Netherlands based.What you will actually be doingThis is not a role where you build clever models that never get used. Your focus is on creating measurable value for clients using data science, machine learning and GenAI, in a consulting and advisory context.You will own work from the very beginning, asking questions like “What value are we trying to create here?” and “Is this the right problem to solve?” through to “It is live, stakeholders are using it and we can see the impact in the numbers.”You will work fairly independently and you will also be someone that more junior team members look to for help and direction. A big part of the job is taking messy, ambiguous business and technical problems and turning them into clear, valuable solutions that make sense to the client.You will do this in a client facing role. That means you will be in the room for key conversations, providing honest advice, managing expectations and helping clients make good decisions about where and how to use AI.What your day to day might look likeGetting to the heart of the problem

Meeting with stakeholders who may not be clear on what they really need

Using discovery sessions, workshops and structured questioning to uncover the real business problem

Framing success in terms of value. For example higher revenue, lower cost, reduced risk, increased efficiency or better customer experience

Translating business goals into a clear roadmap of data and AI work that everyone can understand

Advising clients when AI is not the right solution and suggesting simpler or more cost effective alternatives

Consulting and advisory work

Acting as a trusted advisor to product owners, heads of department and executives

Helping clients prioritise use cases based on value, feasibility and risk

Communicating trade offs in a simple way. For example accuracy versus speed, innovation versus compliance, cost versus impact

Preparing and delivering client presentations, proposals and updates that tell a clear story

Supporting pre sales activities where needed, such as scoping work, estimating effort and defining outcomes

Managing client expectations, risks and dependencies so there are no surprises

Building things that actually workOnce the problem and value are clear, you will design and deliver production ready ML and GenAI solutions. That includes:

Designing and building data pipelines, batch or streaming, that support the desired outcomes

Working with engineers and architects so your work fits cleanly into existing systems

Making sure what you build is reliable in production and moves the needle on agreed metrics, not just offline benchmarks

Explaining design decisions to both technical and non technical stakeholders

GenAI workYou will work with GenAI in ways that are grounded in real use cases and business value:

Building RAG systems that improve search, content discovery or productivity rather than existing for their own sake

Implementing guardrails so models do not leak PII or generate harmful or off brand content

Defining and tracking the right metrics so you and the client can see whether a GenAI solution is useful and cost effective

Fine tuning and optimising models so they perform well for the use case and budget

Designing agentic workflows where they genuinely improve outcomes rather than add complexity

Helping clients understand what GenAI can and cannot do in practice

Keeping it runningYou will set up the foundations that protect value over time:

Experiment tracking and model versioning so you know what works and can roll back safely

CI/CD pipelines for ML so improvements reach users quickly and reliably

Monitoring and alerting for models and data so you can catch issues before they damage trust or results

Communicating operational risks and mitigations to non technical stakeholders in plain language

Security, quality and complianceYou will help make sure:

Data is accurate, traceable and well managed so decisions are sound

Sensitive data is handled correctly, protecting users and the business

Regulatory and compliance requirements are met, avoiding costly mistakes

Clients understand the risk profile of AI solutions and the controls in place

Working with peopleYou will be a bridge between technical and non technical teams, inside our organisation and on the client side. That means:

Explaining complex ML and GenAI ideas in plain language, always tied to business outcomes

Working closely with product managers, engineers and business stakeholders to prioritise work that matters

Facilitating workshops, playback sessions and show and tells that build buy in and understanding

Coaching and supporting junior colleagues so the whole team can deliver more value

Representing the company professionally in client meetings and at industry events

What we are looking forExperience

Around 3 to 6 years of experience shipping ML or GenAI solutions into production

A track record of seeing projects through from discovery to delivery, with clear impact

Experience working directly with stakeholders or clients in a consulting, advisory or product facing role

Education

A Bachelor or Master degree in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics or Engineering

or

Equivalent experience that shows you can deliver results

Technical skillsCore skills

Strong Python and SQL, with clean, maintainable code

Solid understanding of ML fundamentals. For example feature engineering, model selection, handling imbalanced data, choosing and interpreting metrics

Experience with PyTorch or TensorFlow

GenAI specific

Hands on experience with LLM APIs or open source models such as Llama or Mistral

Experience building RAG systems with vector databases such as FAISS, Pinecone or Weaviate

Ability to evaluate and improve prompts and retrieval quality using clear metrics

Understanding of safety practices such as PII redaction and content filtering

Exposure to agentic frameworks

Cloud and infrastructure

Comfortable working in at least one major cloud provider. AWS, GCP or Azure

Familiar with Docker and CI/CD pipelines

Experience with managed ML platforms such as SageMaker, Vertex AI or Azure ML

Data engineering and MLOps

Experience with data warehouses such as Snowflake, BigQuery or Redshift

Workflow orchestration using tools like Airflow or Dagster

Experience with MLOps tools such as MLflow, Weights and Biases or similar

Awareness of data and model drift, and how to monitor and respond to it before it erodes value

Soft skills, the things that really matter

You are comfortable in client facing settings and can build trust quickly

You can talk with anyone from a CEO to a new data analyst, and always bring the conversation back to business value

You can take a vague, messy business problem and turn it into a clear technical plan that links to outcomes and metrics

You are happy to push back and challenge assumptions respectfully when it is in the client’s best interest

You like helping other people grow and are happy to mentor junior colleagues

You communicate clearly in writing and in person

Nice to have, not requiredDo not rule yourself out if you do not have these. They are a bonus, not a checklist.

Experience with Delta Lake, Iceberg, Spark or Databricks, Palantir

Experience optimising LLM serving with tools such as vLLM, TGI or TensorRT LLM

Search and ranking experience. For example Elasticsearch or rerankers

Background in time series forecasting, causal inference, recommender systems or optimisation

Experience managing cloud costs and IAM so value is not lost to waste

Ability to work in other languages where needed. For example Java, Scala, Go or bash

Experience with BI tools such as Looker or Tableau

Prior consulting experience or leading client projects end to end

Contributions to open source, conference talks or published papers that show your ability to share ideas and influence the wider community

Got a background that fits and you’re up for a new challenge? Send over your latest CV, expectations and availability.Staffworx Limited is a UK based recruitment consultancy partnering with leading global brands across digital, AI, software, and business consulting. Let’s talk about what you could add to the mix.

Senior Data Scientist

Senior Data Scientist - Customer Data Salaries in the region of £70,000 - £85,000 DoE Hybrid working - 2/3 days central London office Job Reference J13015 Full UK working rights required/no sponsorship available Immediate requirement - strong leadership skills We are seeking for an experienced, passionate and highly motivated Data Scientist who will help discover the information hidden in vast amounts of customer data, and help make data driven decisions to deliver better products, service and relevance to the customers. Not specifically managing others, but management of your own workload, taking initiative to mould the role into your own and come with a pragmatic mindset. The role • Lead development of machine learning solutions for CRM personalization. • Build and optimize recommendation engines using neural networks and deep learnings, incorporating product embeddings and other advanced features to improve relevance and performance. • Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies • Own the full ML lifecycle-from model design to deployment and monitoring. • Partner with engineering and data teams to ensure scalable solutions. • Continuously monitor and improve model performance using data insights and feedback. Skills • Proven experience in machine learning, particularly in recommendation systems and deep learning architectures. • Strong understanding of two-tower neural networks, embedding techniques, and ranking models. • Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) • Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. • Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. • Ability to work cross-functionally with marketing, CRM, and engineering teams. • Excellent communication and stakeholder management skills • Experience in a global or multi-regional context is a plus If you would like to hear more, please do get in touch. Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK’s leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data. For more information, visit our website: (url removed)

MLOps Tech Lead

Stackstudio Digital Ltd.

+13

Job DetailsRole / Job Title:MLOps Tech LeadWork Location:London, UKOffice Requirement (Hybrid):2 days per weekKey Responsibilities (High-Level) Data Pipeline Development: Lead the technical direction of projects and ensure the use of Sainsbury’s best practices to the best quality. Data Integration: Lead and provide expertise on Integrate data from various sources, ensuring data consistency, integrity, and quality across the entire data lifecycle. Infrastructure Management: Provide guidance for the junior & Mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop).The RoleAs a Tech Lead, you will play a critical role in designing, building, and maintaining data pipelines and infrastructure that enable the development and deployment of machine learning models and drive engineering excellence. You will collaborate closely with data scientists, and lead ML engineers, and software engineers to ensure data is clean, accessible, and optimised for large-scale processing and analysis.Your Responsibilities Data Pipeline Development: Lead the technical direction of projects and ensure the use of Sainsbury’s best practices to the best quality. Data Integration: Lead and provide expertise on Integrate data from various sources, ensuring data consistency, integrity, and quality across the entire data lifecycle. Infrastructure Management: Provide guidance for the junior & Mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop). Data Preparation: Collaborate with data scientists to prepare and transform raw data into formats suitable for machine learning, including feature engineering and data augmentation. Automation: Implement automation tools and frameworks (CI/CD) to streamline the deployment and monitoring of machine learning models in production. Performance Optimisation: Optimise data processing workflows and storage solutions to improve performance and reduce costs. Collaboration: Work closely with cross-functional teams, including data science, engineering, and product management, to deliver data solutions that meet business needs. Mentorship: junior and mid-level data engineers and provide technical guidance on best practices and emerging technologies in data engineering and machine learning and helping to enhance their skills and career growth. Knowledge Sharing and Empowerment: Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews. Innovation and Continuous Improvement: Foster a collaborative and inclusive team environment that encourages continuous learning and improvement.Your ProfileEssential Skills / Knowledge / Experience Knowledge of machine learning frameworks (e.g., PySpark, PyTorch) and model deployment tools (e.g., MLflow, TensorFlow Serving). Strong experience with data processing frameworks (e.g., Apache Spark, Flink). Expertise in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra). Hands-on experience with cloud platforms (e.g., AWS, GCP, Azure) and their data services (e.g., Snowflake, S3, BigQuery, Redshift). Experience with containerisation and orchestration tools (e.g., Docker, Kubernetes). Familiarity with version control systems (e.g., Git) and CI/CD pipelines.Desirable Skills / Knowledge / Experience Certifications: AWS Certified Big Data Specialty, Google Professional Data Engineer, or equivalent.Soft Skills: o Excellent problem-solving and analytical skills. o Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. o Ability to work independently and in a team-oriented, collaborative environment.Leadership and Communication Strong leadership skills with the ability to inspire and guide team. Lead scrum ceremonies as and when needed (Standup, Planning, and grooming sessions). Excellent verbal and written communication skills, with the ability to articulate complex technical concepts. Creating a safe and inclusive environment where all team members feel that their input is valued and are never dissuaded from speaking up or asking questions.Collaborative Attitude Strong team player with a collaborative approach to working with cross-functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame and if not possible clearly sign positing alternative contacts who can guide. Building a community across Media Agency. Contribute to a positive and inclusive atmosphere within the team.Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap.

Python Software Engineer

Python Software Engineer with strong container orchestration and a passion for machine learning is sought by a high growth scale up based near Cheltenham. Working at the forefront of defence and national security innovation this Python Software Engineer will work within a collaborative engineering function to build bleeding edge AI/ ML enabled software solutions that keep millions of people safe. This role would suit software engineers with experience working in an R&D/ innovation focussed environment who are looking for more end to end project exposure and fast track progression opportunity This Python Software Engineer based near Cheltenham should have most of the following key skills:

Solid Python engineering skills

Containerisation (docker, Kubernetes)

Solid general Machine learning skills - PyTorch,Tensorflow etc

NoSQL database experience

Experience working in R&D or innovation focused engineering teams would be a plus

Front end skills would be useful - Angular, React etc

An active SC clearance would be a plus but not essential This Python Software Engineer will receive

Starting salary of up to £75,000

Hybrid working (2 days a week in the office)

Extensive personal development scheme

25 days holiday

10% private pension scheme

Bonus

Private healthcare

Truly autonomous, collaborative culture with extensive growth potential

Regular remuneration reviews So if you are a Python Software Engineer who wants to join a market leading business with innovation at its core please apply now to be considered Cheltenham Research & development, generative AI, machine learning, LLM, Python, NoSQL, PyTorch, Tensorflow, Docker, Kubernetes

Machine Learning Engineer Consultant

Electus Recruitment Solutions

Location: Cambridge, England, United Kingdom Contract: Permanent Salary: Competitive + Excellent Benefits Job Description: Electus Recruitment is seeking a Machine Learning Engineer Consultant to join a dynamic SME that is part of a larger group of companies poised for significant growth. As a Machine Learning Engineer Consultant, you will contribute to innovative projects that protect the UK from emerging threats. Key Responsibilities: Conduct in-depth research into state-of-the-art machine learning techniques and related emerging technologies. Design, develop and implement machine learning models for a variety of tasks, from proof-of-concept to working prototypes. Understand the underlying algorithms, mathematical concepts and workings of machine learning techniques. Collaborate with a multi-disciplinary team of experts to solve complex challenges. Communicate solutions to technical and non-technical stakeholders. Requirements: Strong technical skills and proven track record in machine learning research, with a focus on deep learning techniques and neural network architectures. Experience with machine learning libraries and frameworks such as PyTorch, TensorFlow and Keras; data manipulation libraries such as Pandas and NumPy; and MLOPs tools such as Docker. Experience with emerging machine learning technologies such as RL, XAI and Generative AI including LLMs. Strong coding proficiency in Python. An enquiring mind and a passion for problem-solving. Post-Graduate Degree and research experience or a PhD in a relevant field such as Physics, Mathematics, Computer Science or Engineering. Ability to obtain and maintain UK security clearance. This is an on-site role. A flexible working policy exists however the applicant is expected to be on-site for the majority of the time. “Due to the nature of work undertaken by our client, incumbents of these positions are required to undergo pre-employment screening and must be able to satisfy clearance criteria for UK Security Vetting” Benefits: Competitive salary and benefits package. Opportunity to work on challenging and rewarding projects. Collaborative and supportive work environment. Access to state-of-the-art facilities and resources. Opportunities for professional development and growth. Generous pension scheme. Private medical insurance. Employee assistance program. Company-sponsored social events. Comprehensive relocation package available, if applicable. Join a company that is committed to growth and innovation. They are a dynamic SME with ambitious plans to double their size over the next five years. As part of our client’s team, you can contribute to their success and be part of something truly exciting. To apply please send us your CV highlighting your relevant experience

MLOps Tech Lead

Stackstudio Digital Ltd.

Job Details Role / Job Title: MLOps Tech Lead Work Location: London, UK Office Requirement (Hybrid): 2 days per week Key Responsibilities (High-Level) Data Pipeline Development: Lead the technical direction of projects and ensure the use of Sainsbury’s best practices to the best quality.Data Integration: Lead and provide expertise on Integrate data from various sources, ensuring data consistency, integrity, and quality across the entire data lifecycle.Infrastructure Management: Provide guidance for the junior & Mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop). The Role As a Tech Lead , you will play a critical role in designing, building, and maintaining data pipelines and infrastructure that enable the development and deployment of machine learning models and drive engineering excellence. You will collaborate closely with data scientists, and lead ML engineers, and software engineers to ensure data is clean, accessible, and optimised for large-scale processing and analysis. Your Responsibilities Data Pipeline Development: Lead the technical direction of projects and ensure the use of Sainsbury’s best practices to the best quality.Data Integration: Lead and provide expertise on Integrate data from various sources, ensuring data consistency, integrity, and quality across the entire data lifecycle.Infrastructure Management: Provide guidance for the junior & Mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop).Data Preparation: Collaborate with data scientists to prepare and transform raw data into formats suitable for machine learning, including feature engineering and data augmentation.Automation: Implement automation tools and frameworks (CI/CD) to streamline the deployment and monitoring of machine learning models in production.Performance Optimisation: Optimise data processing workflows and storage solutions to improve performance and reduce costs.Collaboration: Work closely with cross-functional teams, including data science, engineering, and product management, to deliver data solutions that meet business needs.Mentorship: junior and mid-level data engineers and provide technical guidance on best practices and emerging technologies in data engineering and machine learning and helping to enhance their skills and career growth.Knowledge Sharing and Empowerment: Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews.Innovation and Continuous Improvement: Foster a collaborative and inclusive team environment that encourages continuous learning and improvement. Your Profile Essential Skills / Knowledge / Experience Knowledge of machine learning frameworks (e.g., PySpark, PyTorch) and model deployment tools (e.g., MLflow, TensorFlow Serving).Strong experience with data processing frameworks (e.g., Apache Spark, Flink).Expertise in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra).Hands-on experience with cloud platforms (e.g., AWS, GCP, Azure) and their data services (e.g., Snowflake, S3, BigQuery, Redshift).Experience with containerisation and orchestration tools (e.g., Docker, Kubernetes).Familiarity with version control systems (e.g., Git) and CI/CD pipelines. Desirable Skills / Knowledge / Experience Certifications: AWS Certified Big Data Specialty, Google Professional Data Engineer, or equivalent. Soft Skills:o Excellent problem-solving and analytical skills.o Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.o Ability to work independently and in a team-oriented, collaborative environment. Leadership and Communication Strong leadership skills with the ability to inspire and guide team.Lead scrum ceremonies as and when needed (Standup, Planning, and grooming sessions).Excellent verbal and written communication skills, with the ability to articulate complex technical concepts.Creating a safe and inclusive environment where all team members feel that their input is valued and are never dissuaded from speaking up or asking questions. Collaborative Attitude Strong team player with a collaborative approach to working with cross-functional teams within the Media Agency.Open to feedback and willing to provide constructive criticism to others.Be available for the team, responding within a reasonable time frame and if not possible clearly sign positing alternative contacts who can guide.Building a community across Media Agency.Contribute to a positive and inclusive atmosphere within the team. Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels.Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap.TPBN1_UKTJ

Software Development Engineer

ECM Selection (Holdings) Limited

Develop prototype and production software for defence applicationsNr Cambridge, to £55,000 DoE + BenefitsThis growing tech start-up is part of the expanding defence sector. They are developing an AI based platform that integrates with associate hardware products that they are also building. The work is fast-paced and projects are varied from early-stage prototypes to production code. They are looking to recruit a Software Development Engineer and will consider a recently graduated engineer (must be immediately available) or someone with relevant years of industry experience.As part of the company s software team, you would work on projects that integrate software with hardware which can include control hardware platforms, sensors and custom devices. Sensors may be for tracking or optics, and hardware could be for control of complex devices / instrumentation.Requirements:

Strong academic background in computer science, physics, electronics or similar. Ideally a Master s or PhD. Will be able to demonstrate project experience working on software development for hardware (ideally sensors or control systems).

Extensive experience in software engineering using Python.

Experience with Machine Learning and algorithms would be a bonus. Any exposure to TensorFlow or PyTorch would be desirable.

Aptitude to pick up new technologies demonstrated through projects using other technologies, frameworks and tools.

Experience with embedded systems or computer network systems would be advantageous.

Applicants must be eligible for security clearance including being a UK resident for the past 5 years. Candidates on work visas will not be considered.As projects relate to defence applications, all work is onsite. Their offices are just outside of Cambridge (south). No hybrid work options are available. On offer is the opportunity to work on varied projects and be compensated with a competitive salary that reflects your experience level.Another top job from ECM, the high-tech recruitment experts.Even if this job’s not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call ecm or email your CV. We will always ask before forwarding your CV.Please apply (quoting ref: CV27554) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate.

Machine Learning Engineer

ML Engineer - Must hold active DV Clearance This is an exciting time to join a team to help pioneer both customer’s and an AI adoption journey. Not only will you be directly making a huge impact through the solutions you develop, youll be doing it for an organisation who makes a huge impact to the security of the UK. Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements Transition validated experiments into production-ready solutions, working closely with other engineers on deployment and monitoring Build and optimise ML pipelines using AWS services and experiment tracking tools Develop and integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices, including model explainability and fairness assessment Present experiment findings and production outcomes to stakeholders, articulating operational and strategic value Mentor junior colleagues and share learnings across the team You will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models from experimentation to production with appropriate governance and quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help You With Them Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) TPBN1_UKTJ

Machine Learning Engineer

£45,000 - £65,000 GBP £7,000 DV Bonus Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Title: Machine Learning Engineer Area : National Security Projects Location: London (Hybrid) - 3 days per week Security : Eligibility for Developed Vetting Clearance with the UK Government Salary: Up to £65k + £7k annual DV bonus (once obtained) About the Role: We’re seeking Machine Learning Engineers to design and deploy ML models for national security applications. You’ll work on GenAI, LLMOps, and traditional ML solutions using AWS infrastructure, unique datasets collaborating with data scientists and software engineers to build greenfield solutions. What You’ll Do: Build and optimise Machine Learning pipelines Develop LLM-powered solutions and apply responsible AI practices Transition experiments into production-ready solutions Implement experiment tracking and monitoring Collaborate with data scientists and engineers What We’re Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps and GenAI tools (LangChain, LangSmith) Understanding of feature engineering and vector databases Strong grasp of CI/CD practices for ML deployment Why Join Us: Work with niche datasets and cutting-edge tech Hybrid working and flexible benefits £7k tax-free DV bonus once clearance completes Apply today and make a real-world impact. Reference: AMC/JWH/MLEL1 #jawh TPBN1_UKTJ

Deep Learning Researcher

Cambridge / LondonAbout Us: MicroTECH-Global are working with a global leader in advanced computing, with a dedicated research team focused on applying artificial intelligence to next-generation semiconductor design and optimization.Role Overview: We’re seeking a motivated Deep Learning Researcher with a strong background in machine learning, AI, or related fields. Youll contribute to innovative projects in areas such as large language models (LLMs), reinforcement learning, and optimization for chip design and AI system integration.Responsibilities:

Conduct and publish cutting-edge AI/ML research

Design algorithms for chip optimization and intelligent systems

Collaborate with engineering teams to integrate AI into real-world tools

Stay current on AI trends and contribute to open research

Requirements:

PhD or equivalent experience in ML, AI, CS, physics, or mathematics

Strong publication record (NeurIPS, ICML, ICLR, etc.)

Proficient in Python, C++, and deep learning frameworks (e.g., PyTorch, TensorFlow)

Solid grasp of ML techniques; independent and team-oriented mindset

Preferred:

Experience in LLMs, reinforcement learning, or chip design

Familiarity with JAX and optimization frameworks

Why Join Us:

Work on impactful AI research with real-world applications

Collaborate with top researchers in a global team

Flexible hybrid work environment

Opportunities to publish, innovate, and grow professionally

AI Engineer - Contract

AI Engineer – Contract (x2) Rate: £700 per day Contract Length: 3–6 months Location: Flexible / Hybrid (depending on candidate) Morela is supporting an exciting AI startup in the search for two highly skilled AI Engineers with strong Python expertise to support the delivery of a key AI project. These are hands-on contract roles suited to engineers who enjoy building, optimising, and deploying AI solutions in a fast-moving environment. You’ll work closely with product, data, and engineering teams to design and implement machine learning models, contribute to production-ready pipelines, and help scale AI capabilities across the business. Key Responsibilities: Design, build, and deploy machine learning models using Python Develop and optimise data pipelines and model training workflows Collaborate with cross-functional teams to translate requirements into technical solutions Support model evaluation, performance tuning, and monitoring in production Contribute to best practices around code quality, testing, and scalability Required Experience: Proven experience as an AI Engineer or Machine Learning Engineer Advanced Python skills with experience in ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) Strong understanding of machine learning algorithms and applied AI Experience deploying models into production environments Comfortable working in startup or fast-paced delivery environments This is a strong opportunity to join a growing AI startup at a key delivery phase, working on impactful projects and building production-grade AI solutions. If you’re interested or would like more details, please email me at (url removed)

Data Scientist/AI Engineer

Job Title: AI Engineer/Data Scientist Location: Sheffield or Birmingham - 3 days per week in the office - only candidates within commutable distance will be considered by the client Salary/Rate: £500 per day inside IR35 Start Date: 29/01/2026 Job Type: Contract - 6 monthsCompany Introduction We have an exciting opportunity now available with one of our sector-leading financial services clients! They are currently looking for a skilled AI Engineer/Data Scientist to join their team for an initial 6-month contract.Job Responsibilities/Objectives The Onboarding and Know Your Customer Value Stream incorporates onboarding products, platforms, and a delivery capability particularly suited to client-aligned agile delivery at pace. They are investing heavily across these domains with a strategic focus on increasing adoption of AI capabilities through our flagship AI journeys, day-to-day engineering and overall ways of working. To accelerate achieving our vision, we are seeking an experienced AI Engineer to join the Client Services and OBKYC Technology group.

Building production-ready models to drive content extraction and classification from images and text-based sources.

Working closely with business teams to understand requirements and iteratively design and develop solutions.

Collaborative with product managers, technical teams.

Create, test and iterate new and existing products and features.

Designing and building Python/ML/OCR-based components.

Not only supporting the development of the product, but also the full life cycle including the deployment, testing and production support of the application.

Required Skills/Experience The ideal candidate will have the following:

Strong experience in Document AI/Intelligent document processing using traditional models and Generative AI - particularly in using open source models for achieving business outcomes.

Experience delivering to production in Python, with a focus on machine learning, deep learning, natural language processing, generative AI, image processing and OCR all additional positives.

Experience with some of the following frameworks - TensorFlow, Pytorch, Hugging face, Spacy, OpenCV, Regex or equivalents.

Experience delivering safe code to production, focusing on cybersecurity and resilience of the application and APIs.

Desirable Skills/Experience Although not essential, the following skills are desired by the client:

Experience using PostgreSQL for data storage and management.

Proficiency with Azure core services like Azure Virtual Machines and experience with one or all of Azure CLI, Azure Kubernetes Service (AKS) and Azure DevOps

Experience delivering in teams releasing at a high cadence to production.

Machine Learning Engineer

£65,000 GBP Onsite WORKING Location: Central London, Greater London - United Kingdom Type: Permanent An opportunity is available for an experienced Senior Machine Learning Engineer to design, build and operationalise advanced machine learning solutions that directly support UK national security objectives. This role sits within a multidisciplinary AI engineering environment, working closely with Data Scientists, Software Engineers, Product teams and government stakeholders. The Senior ML Engineer will own the journey from experimentation and hypothesis testing through to secure, production-grade deployment, using a modern AWS-based MLOps and LLMOps platform. The Role The successful candidate will balance rapid experimentation with production readiness, prototyping and validating machine learning and generative AI approaches while ensuring successful models integrate seamlessly into live operational systems. This is a high-impact role at a pivotal point in the adoption of AI, machine learning and large language models across critical national systems, offering the chance to deliver real-world outcomes at scale. Key Responsibilities Designing, developing and optimising machine learning models across traditional ML use cases (forecasting, classification, anomaly detection) and GenAI / LLM solutions Leading experimentation cycles, including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standards Transitioning validated experiments into production-ready ML services, collaborating closely with engineering teams on deployment and monitoring Building scalable ML pipelines using AWS services and modern experiment tracking frameworks Developing and integrating LLM-powered capabilities for evaluation, tracing and production monitoring Implementing robust experiment tracking, model versioning and reproducibility, ensuring full auditability Designing feature engineering strategies and contributing to feature store development Monitoring live models, analysing performance and driving continuous improvement Applying responsible AI principles, including explainability, robustness and fairness Communicating experimental results and production outcomes to stakeholders, highlighting operational and strategic value Mentoring junior engineers and promoting best practices across the team About the Candidate The ideal candidate will bring strong hands-on experience in machine learning engineering, with the ability to translate experimental success into reliable, scalable systems. Essential experience includes: Commercial experience developing and deploying machine learning models in Python Proficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Strong experience delivering ML solutions using AWS services (e.g. SageMaker, Lambda, S3) Expertise in experiment design, including hypothesis formulation, A/B testing and statistical evaluation Proven experience moving models from experimentation into production with appropriate governance and quality controls Hands-on experience with MLOps tooling such as MLflow, Weights & Biases or Data Version Control Practical experience building LLM / GenAI applications, including prompt engineering and retrieval-augmented generation (RAG) Familiarity with LLMOps frameworks such as LangChain, LangSmith or LangGraph Understanding of model validation, evaluation techniques and production monitoring Experience working in cross-functional teams from problem definition through to delivery Strong communication skills, with the ability to explain complex concepts to non-technical audiences Sound judgement in applying AI appropriately and recognising when non-AI approaches are more suitable Desirable Experience Advanced LLM techniques, including agents, tool use and agentic workflows Experience with vector databases (e.g. Pinecone, Weaviate, pgvector) Feature store technologies such as Feast or AWS Feature Store Containerisation and orchestration using Docker, Kubernetes or ECS Infrastructure as Code using Terraform or CloudFormation Large-scale data processing frameworks such as Spark or Dask Knowledge of data governance, compliance and regulated environments Experience delivering solutions within highly regulated industries such as government, finance or healthcare Security Clearance This role requires UK Security Clearance. Applicants must already hold clearance or be eligible and willing to undergo the vetting process. Reference: AMC/RHU/MLE #ryhu TPBN1_UKTJ

Machine Learning Research Engineer - NLP / LLM

An incredible opportunity for a Machine Learning Research Engineer to work on researching and investigating new concepts for an industry-leading, machine-learning software company in Cambridge, UK. This unique opportunity is ideally suited to those with a Ph.D. relating to classic Machine Learning and Natural Language Processing and its application to an ever-advancing technical landscape. On a daily basis you will be working on the very cutting-edge of machine-learning including prototyping, building and implementing new approaches to AI problems. Location: Cambridge 3 days in office / 2 days remote Salary: Highly competitive salary + comprehensive benefits Requirements for Machine Learning Research Engineer:

You will have a Ph.D from a world-leading University in a Computer Science, Physics, Maths or similar (we are very keen to hear from those with a Ph.D. directly related to NLP)

Experience weighted more towards classic machine learning than AI Engineering

Strong knowledge in LLMs, NLP and Machine Learning / AI

Excellent academics throughout including a minimum of a 2.1 degree from a leading university, AAB at A-Level

Published papers

Good understanding of software engineering concepts

Experience with machine learning Python frameworks such as PyTorch, Tensorflow and Scikit-Learn

Data Science experience including working with large data sets

Responsibilities for Machine Learning Research Engineer:

Join a team responsible for investigating the latest research in machine learning algorithms largely within the NLP field along with some computer vision

Make suggestions based on the feasibility of research to help shape future projects and products

Prototyping research concepts

Determining output quality, efficiency, and feasibility compared with other techniques

What this offers:

Working for an industry-leading software company who have a fantastic track record of successfully hiring and training graduates

Highly interesting work researching the next phases of cutting-edge, machine-learning software

A good remuneration and benefits package

Applications:If you would like to apply for this unique ML Engineer opportunity, we would love to hear from you. Please send an up-to-date CV via the relevant link. Were committed to creating an inclusive and accessible recruitment process. If you require reasonable adjustments for your application or during the review process, please highlight this by emailing (if this email address has been removed by the job-board, full details for contact are available on our website). Keywords: Python / Deep Learning / Machine Learning / NLP / Natural Language Processing / Computer Vision / Research / Post-Doc / Ph.D. / DPhil / Computer Science / Mathematics / Physics / Engineering/ Text Analytics / Speech processing / Software Engineer / Research / Researching / Journals / AI / Artificial Intelligence / Machine Vision / Neural Networks / Developer / Algorithm ******************************************************************************** RedTech Recruitment Ltd focus on finding roles for people leaving academia entering industry. Even if the above role isnt of interest, please visit our website to see our other opportunities.We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Senior Machine Learning Engineer

Senior Machine Learning Engineer London Are you a Senior ML Engineer who wants to build AI that genuinely matters? Our client is a leading digital technology organisation delivering AI, data, and software solutions to UK public sector and national security customers. They are expanding their machine learning capability and are seeking an experienced engineer to design, evaluate, and deploy production-grade ML and GenAI solutions in high-impact operational environments. What youll be doing: Design and build ML models across forecasting, classification, anomaly detection, and GenAI / LLM use casesLead experimentation cycles: hypothesis, evaluation, iteration, and validationTake successful ML approaches into production, including deployment and monitoringBuild and optimise ML pipelines on AWSDevelop LLM-powered solutions, including evaluation and observabilityApply strong MLOps practices: experiment tracking, versioning, and reproducibilityCommunicate findings clearly to technical and non-technical stakeholdersMentor junior engineers and contribute to team best practicesThis role is for you if you have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow)Production experience with AWS ML services (e.g. SageMaker, Lambda, S3)Proven ability to move models from experimentation into live systemsExperience with MLOps tools (MLflow, Weights & Biases, DVC, or similar)Hands-on exposure to LLM / GenAI applications, including RAGNice to have: Experience with advanced LLM techniques (e.g. agents, tool use)Familiarity with vector databases and feature storesExperience with Docker, Kubernetes, or Infrastructure as CodeImportant: Security clearance required (or eligibility to obtain it).Benefits: Hybrid working with flexibility25 days holiday plus buy/sell optionsCompetitive pension, bonus, and benefitsStrong career development and mentoringOpportunity to work on mission-critical AI supporting UK securityOk, Im in whats next? Please apply with your latest CV.TPBN1_UKTJ

Data Science Engineer

My client is recruiting for a Data Science Engineer to design, develop, and deliver AI and analytics solutions aligned with the organisations Data & AI strategy.Key ResponsibilitiesEnd-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle management of models. Pilot emerging technologies.Experience & Skills2-4 years in production-level AI/ML delivery. Legal/professional services experience is a plus. AI/ML frameworks: PyTorch, TensorFlow, LangChain. Cloud: Azure (preferred), AWS, GCP. MLOps: CI/CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: ETL, governance. Strong coding, communication, and collaboration skills. Strategic thinking, problem-solving, and stakeholder engagement.In accordance with the Employment Agencies and Employment Businesses Regulations 2003, this position is advertised based upon DGH Recruitment Limited having first sought approval of its client to find candidates for this position.DGH Recruitment Limited acts as both an Employment Agency and Employment Business

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