A unique opportunity for an Audio Systems Engineer to join a very early-stage London technology company building a next-generation edge device product currently in stealth. Founded in 2024 by an exceptionally experienced team of product designers and engineers, several of whom have previously built and exited companies for significant sums, this is a genuine ground-floor opportunity to shape a product from first principles.
This is a small, high-calibre team spanning hardware, embedded systems, software and machine learning. They are building something ambitious, technically complex and product-led, with audio forming a central pillar of the roadmap.

Salary: £55,000 to £70,000 per annum + equity + benefits. £55,000 is realistic for someone straight from PhD level with strong relevant foundations.

Location: Central London, 4 days per week onsite.

Requirements for Audio Systems Engineer:

• Strong academic or commercial experience in audio DSP and signal processing
• PhD in Audio Engineering, Signal Processing, Electrical Engineering, Computer Science or similar, or MSc with strong relevant experience
• Top academics throughout including a 2.1 or 1st degree and at least ABB at A Level
• Strong programming skills in C or C++ with experience working in real-time or low-latency environments
• Practical Python experience for analysis, benchmarking and evaluation tooling
• Experience shipping embedded audio systems or major audio subsystems into production, either commercially or through advanced research
• Strong fundamentals in DSP blocks such as filtering, AGC, DRC, noise suppression, VAD or echo control
• Ability to operate effectively in a fast-paced startup environment
• Strong communication skills and ability to collaborate across hardware, embedded and ML or cloud engineers
• Willingness to work onsite in Central London 4 days per week

Experience in the following would be beneficial:

• Audio codecs and streaming pipelines such as Opus, AAC, RTP or WebRTC-style systems
• Hardware-adjacent experience such as I2S, ADC or DAC, DMA, SPI, I2C or UART
• Experience using oscilloscopes or logic analysers
• Audio measurement techniques and designing repeatable evaluation methodologies
• Always-on or low-power audio detection systems
• Familiarity with ML frameworks such as PyTorch or TensorFlow
• Experience with GStreamer, WebRTC audio processing, SpeexDSP, RNNoise or similar

Responsibilities for Audio Systems Engineer:

• Design, implement and tune a robust end-to-end audio pipeline from real-time capture on-device through to cloud-based processing
• Deliver reliable performance in noisy, unpredictable real-world environments
• Implement and optimise DSP components under tight compute and power constraints
• Define objective performance metrics and build repeatable evaluation and regression testing harnesses
• Debug audio issues across the full stack using instrumentation, profiling and lab equipment where required
• Work closely with ML and cloud engineers to enable audio-driven intelligence via offline and online pipelines
• Collaborate with cross-functional teams to balance quality, latency, compute, power and system complexity
• Contribute to engineering best practice, documentation and design discussions as the team scales

What the role offers:

• A genuine greenfield opportunity within a stealth product
• High ownership and influence over the audio subsystem from day one
• Close collaboration with an experienced founding team
• Equity alongside salary
• The opportunity to build intelligent audio systems that unlock richer data insight than video analytics alone

Applications:
If you would like to apply for this unique Audio Systems Engineering role then please send your CV via the relevant links.
We are committed to creating an inclusive and accessible recruitment process. If you require reasonable adjustments for your application, for example due to a disability, please highlight this by separately emailing . If this email address has been removed by the job board, full contact details are available on our website.

Keywords: Audio Systems Engineer / Embedded DSP Engineer / Audio DSP Engineer / Signal Processing Engineer / Embedded Software Engineer / Audio ML Engineer / Edge AI Engineer / Real-Time Systems Engineer / Acoustic Engineer / C++ Engineer / Embedded C Engineer / Audio Software Engineer / C / C++ / Python / DSP / AGC / DRC / VAD / Echo Cancellation / Opus / AAC / WebRTC / RTP / I2S / SPI / I2C / DMA / PyTorch / TensorFlow / GStreamer / SpeexDSP / RNNoise / Audio Engineering / Electrical Engineering / Signal Processing / Computer Science / Acoustics

RedTech Recruitment Ltd focus on finding roles for Engineers and Scientists. Even if the above role is not of interest, please visit our website to see our other opportunities.
We are an equal opportunity employer and value diversity at RedTech. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Lead MLOps Engineer - London - Permanent

?? London, UK
(If you like the sound of this role and want to relocate - the Client is willing to help facilitate this move!)

This is a high-impact role within a fast-growing AI and robotics organisation focused on building advanced, scalable intelligent systems for real-world industrial applications. The position owns the machine learning infrastructure and MLOps foundations as products, platforms, and teams scale.

You will play a key role in transforming machine learning prototypes into reliable production systems, defining pragmatic engineering standards, and enabling fast, safe delivery of ML-powered capabilities. The role combines hands-on engineering, architectural ownership, and close collaboration with engineering and product teams.

Key Responsibilities

• Own and scale the organisation’s ML infrastructure and MLOps foundations
• Design pragmatic, production-ready system architectures that balance speed, reliability, and cost
• Build and maintain CI/CD pipelines for ML workflows and application delivery
• Productionise ML models including training, evaluation, deployment, monitoring, and rollback strategies
• Ensure reliability, observability, security, and performance across ML systems
• Automate infrastructure provisioning, deployments, and environment management using cloud-native tooling
• Partner closely with ML engineers, software engineers, and product teams to deliver ML features end-to-end
• Act as a technical leader through design reviews, mentorship, and by establishing engineering best practices

Required Experience & Skills

• Staff or lead-level experience in MLOps, DevOps, or Infrastructure Engineering, ideally within high-growth or startup environments
• Strong Python skills with hands-on experience using modern ML frameworks (e.g., PyTorch, TensorFlow, or similar)
• Experience working with major cloud platforms (AWS, GCP, or Azure)
• Proven production experience with Docker and Kubernetes
• Strong understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD)
• Experience with Infrastructure as Code tools such as Terraform and Helm
• Solid understanding of data engineering fundamentals and ML lifecycle management
• Ability to design scalable systems without unnecessary complexity
• Strong debugging and problem-solving skills in distributed systems
• Ownership mindset with excellent communication and cross-functional collaboration skills

What’s Offered

• Competitive salary and equity participation
• Paid vacation in line with local labour regulations
• Opportunities for international collaboration and travel
• Office benefits including meals, snacks, and team events

If you are interested - please apply directly!

Randstad Technologies Ltd is a leading specialist recruitment business for the IT & Engineering industries. Please note that due to a high level of applications, we can only respond to applicants whose skills & qualifications are suitable for this position. No terminology in this advert is intended to discriminate against any of the protected characteristics that fall under the Equality Act 2010. For the purposes of the Conduct Regulations 2003, when advertising permanent vacancies we are acting as an Employment Agency, and when advertising temporary/contract vacancies we are acting as an Employment Business.

MLOps Data Engineer
Hybrid 2/3 days London
Outside IR/35

Were looking for a Data Engineer with strong MLOps ownershipsomeone who builds reliable data pipelines and designs, runs, and improves ML pipelines in production. You wont be training models day-to-day like a Data Scientist; instead, youll enable Data Science by delivering high-quality datasets, reproducible training pipelines, robust deployments, and monitoring that keeps ML systems healthy and trustworthy. What youll do

• Design, build, and operate scalable data pipelines for ingestion, transformation, and distribution
• Develop and maintain ML pipelines end-to-end: data preparation, feature generation, training orchestration, packaging, deployment, and retraining
• Partner closely with Data Scientists to productionize models: standardise workflows, ensure reproducibility, and reduce time-to-production
• Build and maintain MLOps automation: CI/CD for ML, environment management, artefact handling, versioning of data/models/code
• Implement observability for ML systems: monitoring, alerting, logging, dashboards, and incident response for data + model health
• Establish best practices for data quality and ML quality: validation checks, pipeline tests, lineage, documentation, and SLAs/SLOs
• Optimise cost and performance across data processing and training workflows (e.g., Spark tuning, BigQuery optimisation, compute autoscaling)
• Ensure secure, compliant handling of data and models, including access controls, auditability, and governance practices

What makes you a great fit

• 4+ years of experience as a Data Engineer (or ML Platform / MLOps Engineer with strong DE foundations) shipping production pipelines
• Strong Python and SQL skills; ability to write maintainable, testable, production-grade code
• Solid understanding of MLOps fundamentals: model lifecycle, reproducibility, deployment patterns, and monitoring needs
• Hands-on experience with orchestration and distributed processing in a cloud environment
• Experience with data modelling and ETL/ELT patterns; ability to deliver analysis-ready datasets
• Familiarity with containerization and deployment workflows (Docker, CI/CD, basic Kubernetes/serverless concepts)
• Strong GCP experience and services such as Vertex, BigQuery, Composer, Dataproc, Cloud Run, Dataplex, Cloud Storage/or at least one major cloud provider, GCP, AWS, Azure
• Strong troubleshooting mindset: ability to debug issues across data, infra, pipelines, and deployments

Nice to have / big advantage

• Experience with ML tooling such as MLflow (tracking/registry), Vertex AI / SageMaker / Azure ML, or similar platforms
• Experience building and maintaining feature stores (e.g., Feast, Vertex Feature Store)
• Experience with data/model validation tools (e.g., Great Expectations, TensorFlow Data Validation, Evidently)
• Knowledge of model monitoring concepts: drift, data quality issues, performance degradation, bias checks, and alerting strategies
• Infrastructure-as-Code (Terraform) and secrets management / IAM best practices
• Familiarity with governance/compliance standards and audit requirements

Hybrid: 1-2 days per week in the office (London)
Permanent
£100k-£150k DOE + Bonus + Benefits

Experis are delighted to be partnering with a leading and well-respected organisation as they continue to invest heavily in Data Science, Artificial Intelligence and Generative AI. We are supporting them in the search for an experienced Lead Data Scientist to shape, scale and lead their enterprise-wide AI capability.

This is a high-impact, strategic role with responsibility for defining the direction of Data Science and AI across the organisation. You will lead the delivery of production-grade ML and GenAI solutions, build a high-performing specialist team, and partner closely with senior stakeholders to drive measurable business value.

What You’ll Be Doing

• Leading the design, development and productionisation of Machine Learning, AI and GenAI solutions across the business.
• Defining technical standards, best practices and governance for Data Science and MLOps.
• Identifying and prioritising high-impact use cases in partnership with Wealth, Enablement and Technology teams.
• Building, mentoring and developing a high-performing Data Science team.
• Embedding modern MLOps practices including CI/CD, model monitoring, feature stores and version control.
• Working closely with Data Engineering, Architecture and Operations teams to ensure scalable, secure deployment.
• Acting as a senior technical authority and thought leader in advanced analytics and AI.
• Championing innovation, experimentation and continuous improvement in AI and analytics delivery.

Experience Required

• Proven experience in Head of or lead-level Data Science, AI or Machine Learning roles within enterprise environments.
• Strong Python and SQL skills, with experience developing production-grade analytical solutions.
• Hands-on experience with cloud platforms (Azure, AWS and/or Snowflake).
• Expertise in modern machine learning frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow).
• Demonstrable experience delivering end-to-end ML and GenAI solutions (including RAG, LLMs, embeddings and vector databases).
• Strong knowledge of MLOps tooling and practices (MLflow, CI/CD, containerisation, monitoring).
• Experience leading, mentoring and developing technical teams.

If you’d like to learn more, please contact Jacob Ferdinand at

Competitive salary up to £140,000- £210,000 + bonus London based (1 day in office per month)

This is a global technology group with an R&D team that moves fast and thinks big. They’re exploring how AI can raise the quality and performance of large-scale digital products, blending hands-on engineering with real research. If you enjoy trying new ideas, you’ll fit in perfectly.

THE COMPANY

This is a global tech organisation with a dedicated R&D function exploring how AI can improve the quality, reliability, and performance of large-scale digital experiences. The team works on forward thinking projects that blend research, experimentation, and hands-on engineering.

THE ROLE

As a Staff ML Engineer, you’ll take the lead on projects focused on anomaly detection in video based or interactive environments. You’ll guide technical direction, support junior engineers, run experiments, and ship models into production.

Specifically, you can expect to be involved in the following:

• Building and improving ML models for anomaly detection
• Leading research work streams
• Scoping, planning, and communicating project direction with stakeholders
• Mentoring juniors
• Working across areas like self supervised learning, multi modal, or vision-language models
• Bringing concepts to life: from research ? prototype ? production

SKILLS & EXPERIENCE

You’ll thrive in this role if you have:

• Experience leading technical delivery or mentoring junior ML engineers
• Strong hands-on ML skills in Python and frameworks like PyTorch or TensorFlow
• A background in anomaly detection, computer vision, or video based ML
• Experience taking ML research or prototypes through to real world deployment
• Either a research grounding (publications, research-led roles) or deep knowledge of gaming/interactive systems

BENEFITS

• Competitive salary
• 1 day per month in the office
• Sponsorship available
• Great feedback and clear process

HOW TO APPLYPlease register your interest by sending your resume to Madison Barlow via the Apply link on this page.

Up to £100,000 + benefitsCentral London (Hybrid - 2-3 days per week in office)

You will be joining this company at an exciting time, as the company is growing it’s AI capabilities from the ground up. You’ll work on impactful AI solutions used across hundreds of locations and by thousands of customers, with full ownership of projects throughout the full process. This will be a hands-on role and requires someone who wants to make a real difference in consumer lives with AI.

The Company

This well-known organisation is undergoing a large digital transformation, investing heavily in AI to improve both internal operations and customer experience. With a newly formed digital leadership team, AI sits at the heart of the company’s long-term strategy, giving you the opportunity to deliver solutions that make a measurable impact at scale.

The Role

As an AI Engineer, you will design, build, and deploy end-to-end AI solutions. You’ll work closely with senior stakeholders, owning projects from discovery through to delivery, and helping translate complex AI concepts into clear, actionable outcomes.

Specifically, you can expect to be involved in the following:

• Build AI products end-to-end, from prototypes to production.
• Work with teams across the business to define problems, test ideas, and measure impact.
• Prepare data and develop models using both classical ML and generative AI.
• Integrate AI into digital products through services, APIs, and safe, compliant guardrails.
• Manage model life cycle and MLOps while sharing best practices and enabling colleagues.

Skills and Experience

The successful AI Engineer will have the following skills and experience:

• Strong Python and SQL experience, ideally with Databricks
• Experience with ML and LLM tools (e.g., scikit learn, XGBoost, PyTorch, TensorFlow, RAG, APIs)
• Comfortable with data engineering basics and MLOps practices
• Experience working with cloud platforms such as Azure, AWS, or GCP

Benefits

The successful Senior AI Engineer will receive the following benefits:

• Salary up to £100,000
• Performance-related bonus
• Hybrid working model
• Comprehensive benefits package including healthcare and pension

How To Apply

Please register your interest by sending your resume to Madison Barlow via the Apply link on this page.

Our client is looking for an experienced Data Scientist to design, build, and optimise machine learning models and advanced analytics solutions that support institutional priorities across a large, complex network. The role blends hands-on data science with strategic impact, using AWS technologies to deliver predictive insights that drive proactive interventions and data-driven decision-making. This is a hybrid role with the expectation of working 2 days pw in the London office.

Skills and experience required:

• Bachelor’s degree in data science, Statistics, Computer Science, Mathematics, or similar
• Experience delivering predictive analytics or machine learning solutions
• Strong skills in Python, SQL, and ML libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow)
• Hands-on experience with AWS ML services (SageMaker, Lambda, Redshift)
• Ability to clearly communicate insights to non-technical stakeholders
• Strong analytical thinking, collaboration skills, and a results-driven mindset

Role responsibilities:

• Build, tune, and maintain predictive and ML models using AWS SageMaker
• Analyse large datasets and perform feature engineering to improve model performance
• Run experiments, test hypotheses, and optimise models for accuracy and value
• Monitor model performance and manage retraining over time
• Collaborate with Data Engineers, BI Developers, and Analysts to integrate outputs into dashboards and reports
• Partner with academic, operational, and IT stakeholders to translate insights into action
• Document models and support knowledge sharing and scalability
• Contribute to the expansion of predictive analytics into advanced ML/AI use cases

Spectrum IT Recruitment (South) Limited is acting as an Employment Agency in relation to this vacancy.

Senior Software Engineer with a solid Python, Node.js, Typescript and Terraform experience ideally gained in a product lead, scale up environment is sought by a high growth B2B generative AI scale up based in central London.

Working at the bleeding edge of generative AI this Senior Software Engineer will play a key role in greenfield innovation utilising the latest technology to design and implement new solutions within the existing platform.

This role would suit an Engineer with a solid product engineering and a real passion for generative AI solution development who is looking to join a multi award winning scale up at the forefront of market innovation.

In return this Senior Software Engineer can expect excellent autonomy with a clear-cut progression pathway within this innovative, knowledge chare driven culture.

This Senior Software Engineer near London should have most of the following key skills:

• Strong full stack JavaScript engineering skills - Node.js, Next.js, React, Typescript etc
• Strong product development using python
• Cloud infrastructure provisioning - Terraform, Ansible, Kubernetes etc
• Strong general cloud skills - Azure, AWS, GCP
• Experience building cloud based products ideally in a scale up environment
• A delivery focused, mission driven personality
• An interest in AI/ automation - Pytorch, TensorFlow, LlamaCPP, Keras etc

This Senior Software Engineer near London will receive:

• Starting salary of up £110,000 base salary
• Bonus scheme
• Long term hybrid working (2 days a week on-site in central London)
• Flexible working hours
• Excellent progression opportunities
• Personal development scheme
• 25 days holiday
• Private pension
• Fast paced, autonomous culture with extensive growth potential
• Regular remuneration reviews

So if you are a Senior Software engineer who loves the idea of joining this product led, high growth AI scale up an exciting phase of their development please apply now to be considered and for more info.

Senior Software Engineer
London (hybrid)
Node.js, Terraform, Ansible, AI, Microservices, CI/CD, Docker, Kubernetes, AWS, next.js, React, Python, Generative AI

Data Scientist / Machine Learning Engineer

Join our team as a Data Scientist / Machine Learning expert in the Analytics department within the business services industry. This permanent position, based in London, offers an opportunity to apply advanced data science techniques to deliver actionable insights.

Client Details

Data Scientist / Machine Learning Engineer

Our client is a well-established organisation within the business services industry. They are a medium-sized entity with a commitment to innovation and excellence in their field, providing a supportive environment for professional growth.

Description

Data Scientist / Machine Learning Engineer

• Develop and implement machine learning models to analyse complex data sets.
• Collaborate with cross-functional teams to identify business challenges and provide data-driven solutions.
• Optimise data pipelines and workflows for improved efficiency.
• Translate analytical findings into clear insights and recommendations for stakeholders.
• Stay updated on the latest advancements in data science and machine learning methodologies.
• Create and maintain detailed documentation of data models and processes.
• Conduct exploratory data analysis to uncover trends and patterns.
• Ensure data quality and integrity throughout all analytics processes.

Profile

Data Scientist / Machine Learning Engineer

A successful Data Scientist / Machine Learning expert should have:

• A strong academic background in data science, computer science, mathematics, or a related field.
• Hands-on experience with AWS ML stack (SageMaker, Lambda, Redshift).
• Proven ability to design and implement machine learning algorithms and models.
• Proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow).
• Strong data analysis, statistical modelling, and experimentation skills.
• Experience with data visualisation tools and techniques.
• Proficiency in programming languages such as Python, R, or similar.
• Knowledge of data processing frameworks and platforms.
• Attention to detail and a methodical approach to problem-solving.

Job Offer

Data Scientist / Machine Learning Engineer

• Competitive salary ranging from 60,000 to 69,000 per annum.
• Comprehensive standard benefits package.
• Opportunity to work in the thriving business services industry.
• Located in the heart of London with excellent transport links.
• Permanent role with opportunities for professional growth and development.

If you are ready to take the next step in your career as a Data Scientist / Machine Learning specialist, we encourage you to apply now!