Python Software Engineer (Machine Learning AWS) Remote UK to £90k

Are you a data savvy Python Software Engineer with experience of implementing ML algorithms into production?

You could be progressing your career in a senior, hands-on role as part of a friendly and supportive international team at a growing and hugely successful European car insurance tech company as they expand their UK presence.

As a Python Software Engineer you’ll join a cross functional team, collaborating with Data Scientists and Machine Learning Engineers on complex insurance underwriting and pricing systems. They’ll be a range of projects with a focus on implementing Machine Learning algorithms into production systems.

There’s a collaborative team Agile environment where you’ll participate in technical discussions and have your voice heard, there’s also opportunities to mentor other more junior team members if desired.

Location / WFH:

The company is a big advocate of flexible working and prides itself on DEI; you can go into the London office as often or as little as desired and can work fully remotely from anywhere in England; you can also work at times that suit you.

About you:

You are a data savvy Python Software Engineer with advanced coding skills

You have experience of across the full lifecycle of ML model development including into production

You’re collaborative, enjoy problem solving and working with others to overcome technical challenges

You have a strong knowledge of AWS

You have a good knowledge of modern software engineering best practices, microservices, TDD / DDD, common Design Patterns

Experience with Databricks, PostgreSQL, Amazon RedShift or MLflow would be great but not essential

What’s in it for you:

As a Python Software Engineer (Machine Learning AWS) you will earn a competitive package:

Up to £90k salary

Remote working including flexible working hours

Workplace nursery scheme

Enhanced maternity package

25 days holiday plus ability to buy or sell 5 days p/year + extra ‘duvet day’

Pension, Private Medical and Dental Insurance, Life Assurance, Employee Assistance Programme

Weekly Yoga and monthly Acupuncture sessions, Headspace membership

Diverse, inclusive team environment with a range of support networks

A range of other perks including Perkbox, cycle to work, season ticket loan

Apply now to find out more about this Python Software Engineer (Machine Learning AWS) opportunity.

At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We’re an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values.

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£Up to £65,000 GBP Competitive Bonus Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Machine Learning Engineer Join a high-impact AI and data science consultancy recognised for delivering exceptional outcomes across National Security, Defence, Space, and government sectors. This is a unique opportunity to work on cutting-edge AI and machine learning projects that make a tangible difference in the UK, supporting critical national security initiatives. As a Machine Learning Engineer , you will design, develop, and deploy machine learning models that address some of the most complex challenges in national security. You will work in a consultative, hands-on role, collaborating with data scientists, software engineers, product managers, and stakeholders across the full lifecycle, from hypothesis through to production deployment. Due to the sensitive nature of this work, candidates must be willing to undergo DV (Developed Vetting) security clearance , be sole British nationals , and have not spent more than 29 consecutive days outside the UK in the last 5 years . Please note that this role does not provide visa sponsorship and is not open to applicants on Skilled Worker or Dependent visas. This role offers the opportunity to deliver real-world impact, working with diverse data types - including text, images, audio, video, and geospatial data - while applying cutting-edge methods in AI, machine learning, and MLOps/LLMOps practices. You’ll have the opportunity to: Work alongside leading data scientists, ML engineers, and AI researchers on national security projects Design, develop, and iterate on machine learning models for traditional ML use cases and GenAI/LLM applications Explore and implement ML and LLM models on complex, multi-modal datasets Apply modern MLOps/LLMOps practices, including experiment tracking, versioning, and deployment on cloud platforms Influence technical direction and best practice in ML and AI engineering Mentor and support junior engineers and graduates Engage directly with clients to scope, design, and deliver operationally-ready AI and ML solutions Key Responsibilities: Design, develop, and deploy machine learning models for forecasting, classification, anomaly detection, and LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly Transition validated experiments into production-ready solutions, working closely with other engineers on deployment and monitoring Build and optimise ML pipelines using cloud-based platforms and experiment tracking tools Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices, including model explainability, fairness, and ethical considerations Present experiment findings and production outcomes to stakeholders, articulating operational and strategic value Mentor junior colleagues and share learnings across the team Key Requirements: Willingness to undergo DV (Developed Vetting) security clearance Sole British national with no more than 29 consecutive days outside the UK in the last 5 years Proven experience as a Machine Learning Engineer or equivalent role Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Ability to absorb complex scientific and technical concepts and apply them to operational solutions Strong communication skills for both technical and non-technical stakeholders Curiosity, adaptability, and a desire to deliver real-world impact You will gain exposure to: Advanced ML and LLM methods applied to national security challenges Deployment of ML models at scale using cloud platforms and MLOps/LLMOps pipelines A broad range of data types, including text, images, audio, video, and geospatial data Ethical, privacy, and security considerations in AI/ML applications High-impact projects with government and defence clients Mentorship and development opportunities within a diverse, innovative environment Why Join: Work on high-impact projects that directly support national security Gain deep exposure to cutting-edge ML, LLM, and AI technologies Accelerate your career in a supportive, high-performance consultancy Be part of a culture that values innovation, collaboration, and engineering excellence Interested? Apply Now! Reference: AON/AMC/PGMachineLearning #aaon TPBN1_UKTJ

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 About You 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) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures 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) Familiarity with Infrastructure as Code (Terraform, CloudFormation) Experience with data processing frameworks (Spark, Dask) for large-scale workloads Understanding of data governance and compliance frameworks TPBN1\_UKTJ

1000 - 1100 per day INSIDE IR35

Contract: 3 days per week - 1 day per week in london

3 months

Role Purpose

TXP has been engaged to support an early-stage programme shaping. This Senior Data & AI Strategy Consultant will lead a comprehensive review of our clients data landscape, analyse business and technical requirements across all delivery streams, and produce a clear roadmap with prioritised recommendations to support decision-making ahead of programme launch.

This role requires someone who can operate at the intersection of enterprise data strategy, AI capability development and consulting delivery. The successful candidate will combine deep technical fluency in modern data and AI platforms with a track record of building and scaling data practices in complex regulated environments.

Essential Skills & Experience

• Proven senior leadership in data strategy, enterprise data consulting, AI/ML capability development or data practice leadership within professional services or technology consulting
• Demonstrated success building and scaling multi-disciplinary data and analytics teams (from inception to 50+ people) in high-growth consulting environments
• Deep technical fluency across modern data and AI stacks including cloud-native architectures (Azure, AWS), data platforms (Databricks, Snowflake, Microsoft Fabric), ML/AI tools (MLflow, LLMs, RAG pipelines, vector stores) and analytics technologies (Power BI, Tableau)
• Experience reviewing end-to-end data programmes and defining future-state delivery models in regulated or public sector environments
• Ability to translate complex organisational data requirements into clear delivery plans, roadmaps and actionable recommendations at board level
• Strong stakeholder engagement skills with experience advising senior programme leadership, C-suite executives and board-level decision makers

Desireable Experience

• Experience with Microsoft Fabric, OneLake architecture and Azure AI Foundry
• Experience designing AI governance frameworks, model risk management and Responsible AI controls
• Background in delivering MLOps, intelligent document processing (IDP) or LLM-based solutions at enterprise scale

Certain Advantage are recruiting on behalf of our Trading client for an AI Engineer on a contract basis for 6-12 months initially in London. This will require some onsite days in Central London during the week. We are seeking Engineers skilled in python with a strong focus on GenAI AI and LLMs to lead the integration of cutting-edge language technologies into real-world applications. If you’re someone passionate about building scalable, responsible, and high-impact GenAI solutions then this could be for you! We’re looking for Engineers offering competent core technical skills in Python Programming, Data Handling with NumPy, Pandas, SQL, and use of Git/GitHub for version control. Any experience with these GenAI Use Cases would be relevant and desirable; Chatbots, copilots, document summarisation, Q&A, content generation. To help make your application as relevant as possible, please ensure your CV demonstrates any prior experience you have relating to the below; System Integration & Deployment Model Deployment: Flask, FastAPI, MLflow Model Serving: Triton Inference Server, Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex – for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise dataMLOps & Infrastructure MLOps: Model versioning, monitoring, logging Bias Detection & Mitigation Content Filtering & Moderation Explainability & Transparency LLM Safety & Guardrails: Hallucination mitigation, prompt validation, safety layers Azure Cloud Experience Collaboration & Delivery Cross-functional Collaboration: Working with software engineers, DevOps, and product teams Rapid Prototyping: Building and deploying MVPs Understanding of ML & LLM Techniques: To support integration, scaling, and responsible deployment Prompt Engineering: Designing and optimising prompts for LLMs across use cases Model Evaluation & Monitoring Evaluation Metrics: Perplexity, relevance, response quality, user satisfaction Monitoring in Production: Drift detection, performance degradation, logging outputs Evaluation Pipelines: Automating metric tracking via MLflow or custom dashboards A/B Testing: Experience evaluating GenAI features in production environments Does this sound like your next career move? Apply today! Working with Certain Advantage We go the extra mile to find the best people for the job. If you’re hunting for a role where you can make an impact and grow your career, we’ll work with you to find it. We work with businesses across the UK to find the best people in Finance, Marketing, IT and Engineering. If this job isn’t for you, head to (url removed) and register for job alerts and career guidance tips

AI Engineer - Greenfield AI Project - Leeds (Hybrid) Up to £35,000 My client is seeking Graduates with 18 months+ commercial software experience with an interest in AI, ideally some exposure through personal projects or commercial exposure.

ABOUT THE CLIENT

Due to continued growth, we’re recruiting on behalf of an established Leeds-based software house embarking on a greenfield AI project. This is an opportunity to join at the very start of a new AI function, working closely with senior engineers to shape intelligent products from the ground up.

The organisation has a strong engineering culture, modern tech stack, and a track record of delivering scalable software solutions across multiple sectors.

THE BENEFITS

* Hybrid working from their Leeds office * Dedicated learning and development budget * Mentoring from experienced AI and Software Engineers * Clear progression pathway as the AI capability grows * Exposure to real-world AI deployment in production environments

THE AI ENGINEER ROLE

As an AI Engineer, you’ll join a collaborative engineering team working on the design and development of AI-driven features within a brand-new platform. This is a hands-on role where you’ll contribute to model development, data processing pipelines, and integration of AI services into production systems.

You’ll work closely with software engineers, product teams, and stakeholders to help translate business requirements into scalable AI solutions. Given the greenfield nature of the project, you’ll have genuine influence on tooling, frameworks, and best practice from day one.

AI ENGINEER - ESSENTIAL SKILLS

* Degree in Computer Science, Data Science, AI, or similar * Around 18 months’ commercial experience in a software or AI-focused role * Ideally strong Python development skills * Experience working with data processing and APIs * Understanding of machine learning fundamentals * Familiarity with version control (Git) and Agile environments

TO BE CONSIDERED:

Please either apply through this advert or email me directly via . For further information please call me on 0113 887 8355 / 07441 348 209. By applying for this role, you give express consent for us to process and submit (subject to required skills) your application to our client in conjunction with this vacancy only.

KEY SKILLS

AI, Python, Machine Learning, Software Engineering, Data, APIs, Cloud, Agile, Python, TensorFlow, PyTorch, Scikit-learn, XGBoost, NLTK, OpenAI, LangChain, Pandas, NumPy, MLflow, Kubeflow, Docker, Kubernetes, Azure Machine Learning, Google Vertex AI

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DV Data ScientistLocation: RAF Wyton, Huntingdon (45 days onsite)Clearance: Active DV EssentialContract: 12 months Inside IR35 (extension likely up to 3 years) or Permanent roleRate: Negotiable
Programme Overview
Arqtech Search is supporting a defence delivery partner on a secure data transformation programme within an RAF operational environment. The programme focuses on designing, sustaining and evolving secure data platforms that underpin intelligence, surveillance and operational decision-support capabilities. The Data Scientist will play a critical role in delivering resilient, maintainable, and scaleable AI solutions.

Key Responsibilities

• Maintain and continuously improve the AS AI computer vision model operating in production.
• Support and manage the COTS model to ensure consistent performance.
• Expand the solutions functionality through ongoing development, introducing additional features and new use cases.
• Uphold adherence to security, ethical, and regulatory requirements.
• Deliver AI solutions that are robust, maintainable, and scalable.

Required Skills

• Programming: Advanced proficiency in Python.
• ML Engineering & MLOps: Hands-on experience with widely used ML tooling (e.g., MLflow, Airflow, Docker, Kubernetes).
• CI/CD & DevOps: Familiarity with CI/CD workflows and automation tools (e.g., GitLab, Jenkins) for streamlined deployments.
• Data Engineering Fundamentals: Knowledge of ETL (Extract, Transform, Load) processes, data warehousing, and streaming architectures.
• System Architecture: Experience designing and implementing scalable, cloud-native pipelines and systems.

Due to nature of this work, active DV clearance is essential and 5 days per week are required on-site in RAF Wyton for a 9 day condensed working week (every other Friday off).We cannot consider candidates who do not currently hold an active DV clearance.

Location: Erskine, Scotland (Hybrid 2/3 days per week in the office)
Candidates must be eligible for clearance.

DXC Technology (NYSE: DXC) is a leading independent, end-to-end IT services company, helping organisations harness innovation to thrive through change. Serving nearly 6,000 private and public sector clients across 70 countries, DXC combines technology independence, global talent, and an extensive partner network to deliver next-generation IT services and solutions.

We are proud to be recognised globally for corporate responsibility and inclusive workplace practices.

The Role

Are you passionate about bringing machine learning solutions into real-world production environments? Do you enjoy collaborating with others to build scalable, reliable systems?

We are looking for a Machine Learning Ops Engineer to join our growing team. This role is ideal for someone who enjoys solving complex problems, working cross-functionally, and continuously developing their technical expertise in a supportive environment.

If you dont meet every single requirement listed below, we still encourage you to apply. We value potential, curiosity, and a willingness to learn.

What Youll Be Doing

• Deploying, monitoring, and scaling machine learning models in production.
• Collaborating with data scientists, engineers, and stakeholders to integrate AI solutions into scalable products.
• Supporting the full ML lifecycle, from experimentation to deployment and optimisation.
• Applying best practices in data engineering and contributing to architectural decisions.
• Using modern MLOps tools and CI/CD approaches to improve reliability and efficiency.
• Contributing to a culture of knowledge-sharing and continuous improvement.

Technical Experience

Were looking for experience in many of the following areas:

• Strong Python skills and familiarity with ML libraries such as Pandas, NumPy, and scikit-learn.
• Experience with frameworks such as TensorFlow, Keras, or PyTorch.
• Exposure to gradient boosting tools such as XGBoost, LightGBM, or CatBoost.
• Experience with model deployment tools (e.g., ONNX, TensorRT, TensorFlow Serving, TorchServe).
• Familiarity with ML lifecycle tools such as MLflow, Kubeflow, or Azure ML Pipelines.
• Experience working with distributed data processing (e.g., PySpark) and SQL.
• Understanding of software engineering best practices, including version control (Git).
• Knowledge of CI/CD principles in ML environments.
• Experience with cloud-native ML platforms is advantageous.

What Were Looking For

• A collaborative mindset and strong communication skills.
• A thoughtful, structured approach to problem solving.
• A commitment to continuous learning and professional growth.
• The confidence to contribute ideas while valuing diverse perspectives.

Why Join Us?

• Work on meaningful AI projects with real-world impact.
• Join a supportive, forward-thinking team that values inclusion and diverse perspectives.
• Access structured learning, mentoring, and career development opportunities.
• Flexible hybrid working arrangements.
• A workplace culture that supports wellbeing and work-life balance.

What We Offer

• Competitive salary.
• Pension scheme.
• DXC Select comprehensive benefits package including private medical insurance, gym membership, and more.
• Perks at Work discounts on technology, groceries, travel and more.
• DXC incentives recognition tools, employee lunches, and regular social events.

Ready to Shape the Future of AI?

We are committed to building diverse teams and creating an inclusive environment where everyone can thrive. If this role excites you, wed love to hear from you.

Apply today and bring your skills, perspective, and ambition to a team that values innovation, collaboration, and growth.

• Role/Job title: AI Architect
• Mode of working London- 3 days onsite
• Type of Employment- Permanent

The Role:

As an Artificial Intelligence Architect, you will lead client-facing initiatives at the forefront of Generative and Agentic AI. This high-impact, senior consulting role blends visionary thinking with deep technical expertise, solution architecture, and strategic advisory. You will be instrumental in shaping innovative AI solutions that drive transformation across enterprise environments.

Your Responsibilities:

• Client Engagement: Partner with sales leaders to qualify opportunities, shape proposals, and build compelling business cases. Act as a trusted advisor to clients during discovery sessions, workshops, and bid processes.
• Solution Design: Translate client needs into fit-for-purpose Data & AI solutions, leveraging modern cloud platforms (Azure/AWS, with GCP/Oracle as a plus). Design AI interventions for application support, monitoring, and business operations.
• Technical Leadership: Lead complex implementations that deliver measurable outcomes. Architect and scale GenAI chatbots and Agentic AI solutions. Evaluate and select appropriate models, frameworks, and orchestration tools.
• Thought Leadership: Produce thought leadership content, refine go-to-market propositions, and maintain strong knowledge of the competitive landscape.
• Collaboration: Work closely with cross-functional teams-including data science, engineering, and business stakeholders-to identify opportunities and design robust AI solutions. Foster cross-functional collaboration between various stakeholders like business, data science, and engineering.
• Innovation: Contribute to overall account strategy, ensuring technical solutions align with business priorities. Drive productivity and cost optimizations.

Your Profile:

Essential skills/experience/knowledge:

• Experience in architecting and solutioning in Gen AI, Agentic AI, classic ML, and automation space.
• Good understanding of Prompt engineering, RAG pipelines, Supervised/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability.
• Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS, etc.).
• Ability to design enterprise-level AI/Gen AI platform/solutions with the client’s existing enterprise stack.
• Hands-on mastery of core GenAI frameworks (e.g., LangChain, LlamaIndex) and practical experience with Agentic AI frameworks and concepts (e.g., AutoGen, CrewAI, LangGraph).
• Strong working knowledge and practical deployment experience on at least one major cloud platform (AWS, Azure, GCP), including their AI/ML services.
• Strong foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems.
• Proficiency in Python with AI/ML frameworks (PyTorch, TensorFlow).
• Experience with MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes).
• Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK).
• Proven experience developing applications leveraging state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude) including prompt engineering, fine-tuning, and evaluation.
• Strong grasp of advanced techniques such as complex task decomposition for agents, reasoning engines, knowledge graphs, autonomous agent design, and evaluation methodologies for complex AI systems.
• Strong articulation, stakeholder management, and consulting skills. Experience working on client proposals RFI/RFP/Orals stages.
• Experience leading a team of AI/software engineers.

Rewards & Benefits:

TCS is consistently voted a Top Employer in the UK and globally. Our competitive salary packages feature pension, health care, life assurance, laptop, phone, access to extensive training resources and discounts within the larger Tata network.

We offer health & wellness initiatives and sports events; we are the proud sponsor of the London Marathon.

Location: Erskine, Scotland - Hybrid Candidates must be eligible for clearance Were looking for a talented and motivated Machine Learning Engineer to join our growing team. This is an exciting opportunity for women who want to advance their career in AI/ML, work on meaningful projects, and thrive in a supportive, collaborative environment. What Youll Do: Design, develop, and deploy machine learning models using modern frameworks and libraries. Collaborate closely with data scientists, engineers, and stakeholders to turn ideas into impactful solutions. Optimize and deploy models with tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate ML solutions into production environments. Monitor and improve model performance to ensure accuracy and efficiency. Contribute to team knowledge by mentoring and supporting colleagues. Bring creativity and fresh perspectives to problem-solving and technical solutions. What Were Looking For: We welcome applications from women who are passionate about machine learning and eager to grow: Strong Python skills and experience with ML libraries (pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, Keras, PyTorch). Familiarity with model deployment and serving tools (ONNX, TensorRT, TensorFlow Serving, TorchServe). Experience with ML lifecycle tools (MLflow, Kubeflow, Azure ML Pipelines). Knowledge of distributed data processing (PySpark) and software engineering principles (Git). A collaborative mindset and excellent problem-solving abilities. Experience in data cleansing, exploratory data analysis, and visualisation. A continuous learning mindset and interest in emerging AI/ML technologies. Why Join Us? Work on impactful AI projects with real-world applications. Be part of a collaborative and forward-thinking team. Access to continuous learning and development opportunities. Flexible working arrangements and a supportive work culture. TPBN1\_UKTJ

Data Scientist - Optimisation & Operations Research

North West London (Hybrid, 3 days on-site) | £550 - £750/day

The Opportunity

We’re recruiting on behalf of a globally recognised organisation undergoing a major transformation in how it uses data to drive operational decisions. This is a rare chance to work on genuinely complex, high-impact decision-support software - embedding cutting-edge optimisation and machine learning directly into live operations.

You’ll join a high-performing, Agile product squad as a full-stack Data Scientist, sitting at the intersection of data engineering, ML, and operations research.

What You’ll Be Doing

• Designing and delivering optimisation and ML models (linear/mixed-integer programming, heuristics, supervised/unsupervised learning) in Python, from prototype to production
• Building robust, automated data pipelines and integrating models into cloud-based deployment pipelines with CI/CD
• Owning features end-to-end - from stakeholder requirements through to algorithm hardening, edge-case handling, and value measurement
• Working with orchestration frameworks (Dagster/Airflow), experiment tracking (MLflow), and containerised infrastructure (Docker/ECS)
• Collaborating closely with business stakeholders and contributing to roadmap and feature prioritisation

What We’re Looking For

• Strong operational research and optimisation background - this is a must
• Fluent Python, with hands-on experience of scikit-learn, pandas, numpy, Gurobi or similar OR packages
• Production ML/optimisation software experience - you’ve shipped models that run at scale
• Cloud platform experience (AWS preferred); familiarity with SageMaker, DVC, GitHub Actions a bonus
• Strong SQL and data engineering fundamentals
• Experience in airline, aviation, transport, or engineering/maintenance environments is highly desirable
• Master’s degree (or equivalent) in Data Science, ML, or Operational Research - or strong demonstrable industry experience

Data Scientist - Optimisation & Operations Research North West London (Hybrid, 3 days on-site) | £550 - £750 /day The Opportunity We're recruiting on behalf of a globally recognised organisation undergoing a major transformation in how it uses data to drive operational decisions. This is a rare chance to work on genuinely complex, high-impact decision-support software - embedding cutting-edge optimisation and machine learning directly into live operations. You'll join a high-performing, Agile product squad as a full-stack Data Scientist, sitting at the intersection of data engineering, ML, and operations research. What You'll Be Doing Designing and delivering optimisation and ML models (linear/mixed-integer programming, heuristics, supervised/unsupervised learning) in Python, from prototype to production Building robust, automated data pipelines and integrating models into cloud-based deployment pipelines with CI/CD Owning features end-to-end - from stakeholder requirements through to algorithm hardening, edge-case handling, and value measurement Working with orchestration frameworks (Dagster/Airflow), experiment tracking (MLflow), and containerised infrastructure (Docker/ECS) Collaborating closely with business stakeholders and contributing to roadmap and feature prioritisation What We're Looking For Strong operational research and optimisation background - this is a must Fluent Python, with hands-on experience of scikit-learn, pandas, numpy, Gurobi or similar OR packages Production ML/optimisation software experience - you've shipped models that run at scale Cloud platform experience (AWS preferred); familiarity with SageMaker, DVC, GitHub Actions a bonus Strong SQL and data engineering fundamentals Experience in airline, aviation, transport, or engineering/maintenance environments is highly desirable Master's degree (or equivalent) in Data Science, ML, or Operational Research - or strong demonstrable industry experience

Generative AI Leader / Lead Generative AI Engineer / AI Architect / Generative AI Lead / Gen AI Lead / AI Architect

Location: South West, UK (Hybrid Working)
Salary: Up to £150,000 + package
Company: Hiring on behalf of a client via 167 Solutions Ltd

167 Solutions Ltd is partnering with an innovative organisation in the South West to appoint a Generative AI Leader. This is a senior, high-impact role for a visionary who can operate both as a trusted advisor to executive stakeholders and as a hands-on technical leader driving delivery of enterprise-grade AI solutions.

The Opportunity

You will define and lead the organisations Generative AI strategy, translating cutting-edge capabilities into real business value. The role requires a rare blend of commercial advisory expertise, architectural oversight, and technical delivery leadership across large-scale AI programmes.

Key Responsibilities

• Define and execute the enterprise Generative AI strategy aligned to business objectives
• Advise C-suite and senior stakeholders on AI adoption, governance, risk, and value realisation
• Lead the design, architecture, and delivery of GenAI solutions from concept to production
• Establish AI operating models, best practices, and responsible AI frameworks
• Build and lead high-performing multidisciplinary teams (Data Science, ML Engineering, MLOps)
• Identify use cases across functions (customer experience, operations, knowledge management, automation)
• Ensure scalability, security, and compliance of AI platforms

Required Experience

• Proven leadership delivering Generative AI programmes at enterprise scale
• Strong advisory background engaging senior business leaders
• Deep technical expertise across modern AI/ML ecosystems
• Track record of translating emerging technologies into measurable outcomes

Technical Expertise

Generative AI & LLMs

• Large Language Models (GPT, Claude, Llama, Mistral or similar)
• Prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation)
• Multimodal AI (text, image, audio, video)
• Agentic frameworks and orchestration

AI/ML Engineering

• Python, PyTorch, TensorFlow, JAX
• NLP, deep learning, model optimisation
• Evaluation frameworks and guardrails

Data & Platforms

• Vector databases (Pinecone, Weaviate, FAISS, Milvus)
• Knowledge graphs and semantic search
• Data engineering pipelines

MLOps & Deployment

• CI/CD for ML, model monitoring, versioning
• Kubernetes, Docker, serverless architectures
• MLflow, Kubeflow, SageMaker or similar

Cloud & Architecture

• Azure AI, AWS AI/Bedrock, Google Vertex AI
• API-led architectures and microservices
• Security, governance, and responsible AI

Frameworks & Tooling

• LangChain, LlamaIndex, Semantic Kernel or equivalent
• Integration with enterprise systems (CRM, ERP, collaboration platforms)

Desirable

• Experience in regulated environments
• AI ethics, governance, and compliance knowledge
• Background in consulting or digital transformation

Why Apply

This is a rare opportunity to shape AI strategy at scale while remaining close to delivery. You will influence how an organisation embeds Generative AI into its core operations and future growth.