1 to 25 of 566 Remote/Hybrid Machine Learning Jobs in the UK

advanced machine learning and computer vision models used within clinical research and drug development. The business is building large-scale, production-grade ML systems applied to complex 3D imaging data. This role is highly engineering-focused, sitting between machine learning, infrastructure and deployment. You will work … closely with ML Scientists and engineering teams to ensure models can be trained and deployed reliably at scale. Location: 1 day per week in London - Shepherd's Bush (4 days remote) Salary: £70,000 £90,000 per annum, with flexibility for the right candidate, plus benefits Requirements for Senior/ ...

title: Senior Machine Learning Research Engineer Salary: £64,490 - £86,255 Location: Cambridge - Triangle/Hybrid (2 days per week in the office) Contract: Permanent Hours: Full Time (35 hours per week) Shape the future of AI-powered learning solutions with Cambridge University Press & Assessment, a world … solutions in production environments. Strong track record of successfully translating academic research into real-world applications and products. Ability to estimate suitability of candidate ML, NLP, LLM, and GenAI technologies for specific scenarios, estimate the time, cost and outcomes of different solutions, and apply effective risk management to ensure prompt ...

Machine Learning Operations Engineer Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London. To be considered for the role you must have … within the company. Technical Skills required Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity ...

reliability, and performance Partner closely with data scientists to turn experimental models into well-engineered, production-ready systems Develop and maintain end-to-end ML pipelines, including feature engineering, training, evaluation, versioning, monitoring, and automated retraining Contribute to MLOps capabilities, including CI/CD pipelines, model registries, infrastructure automation … fairness analysis, and performance optimisation Collaborate with data engineers and architects to enhance data quality, data flows, and platform capabilities Lead experimentation using modern ML frameworks to assess new algorithms and technologies and make recommendations on adoption Support model governance processes, ensuring compliance with internal standards, documentation, transparency, and regulatory ...

model capability. THE ROLE As a Staff Machine Learning Engineer you will... Lead the design, development, and deployment of end-to-end ML solutions. Architect scalable ML systems and pipelines that integrate seamlessly with cloud infrastructure. Mentor engineers, championing best practices across coding, experimentation, and MLOps. Collaborate with … Product and Engineering teams to define priorities and model strategy. Apply deep learning, NLP or classical ML techniques to real-world, high-impact problems. Uphold responsible AI principles across model development and evaluation. YOUR SKILLS & EXPERIENCE The successful Staff Machine Learning Engineer will have: Strong Python skills ...

same! Key Responsibilities: Build, maintain, and productionise machine learning models using PyTorch or similar frameworks. Design and optimise data pipelines for ML inference at scale. Work with large datasets using Big Data tools. Deploy ML workflows using AWS infrastructure . Collaborate with data engineers and product teams … integrate ML solutions into RealityMine’s products. Investigate and troubleshoot customer feedback on data quality and drive model improvements from experimentation . Promote best practices in ML engineering and data quality across the business. Adhere to Company Policies and Procedures with respect to Security, Quality and Health & Safety. AI first ...

same! Key Responsibilities: Build, maintain, and productionise machine learning models using PyTorch or similar frameworks. Design and optimise data pipelines for ML inference at scale. Work with large datasets using Big Data tools. Deploy ML workflows using AWS infrastructure . Collaborate with data engineers and product teams … integrate ML solutions into RealityMine’s products. Investigate and troubleshoot customer feedback on data quality and drive model improvements from experimentation . Promote best practices in ML engineering and data quality across the business. Adhere to Company Policies and Procedures with respect to Security, Quality and Health & Safety. AI first ...

Role : Machine Learning Infrastructure Developer Location: Cambridge, UK (Hybrid ) Duration: 12 Months Responsibilities: Create robust, flexible, and scalable machine learning tooling and infrastructure that supports research scientists in leveraging large-scale internal infrastructure (e.g., source control, distributed compute clusters, data storage). Work collaboratively as part … signal processing experience . Experience collaborating closely with research users or internal customers to deliver robust, stable, and scalable tooling. Experience writing scalable ML pipelines or tooling used by research teams. Familiarity with Linux or Windows shell scripting. ...

Junior ML Operations Engineer (Python) Salary: Up to £40,000 depending on experience Location: Manchester - (Hybrid working - currently 40% on site increasing to 60% within 12 months) Ref: J13059 This is an exciting opportunity to build a career in production machine learning within a large scale pricing … will be supported by experienced engineers, exposed to modern tooling, and given the space to build confidence in production machine learning and ML Operations. This role is designed to set strong foundations for long term technical growth. Right to work You must be eligible and authorised to work ...

+ £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 … 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 ...

backing for data-driven decision-making, they are now looking for a Machine Learning Engineer to help operationalise, maintain, and optimise their ML systems across the organisation. This position is ideal for someone who is strong technically, resilient, enjoys problem-solving in ambiguous environments, and wants to work … closely with both Data Scientists and Engineers. Key Responsibilities Deploy, productionise, and monitor machine-learning models across the business. Maintain and improve ML infrastructure to ensure high reliability, scalability, and runtime performance. Collaborate with data scientists to ensure smooth model handover from prototype to production. Work alongside data ...

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 ...

with a UK-based advanced technology organisation expanding its machine learning capability. The team works on non-trivial, real-world problems where ML is applied in technically challenging environments rather than consumer-facing products. This role sits between research and engineering, focusing on taking ML concepts and adapting … with engineers and researchers across disciplines What We’re Looking For Strong foundations in machine learning Hands-on Python experience with modern ML frameworks Comfortable working on open-ended technical problems Strong STEM background (degree or equivalent experience) Security Clearance Candidates must be eligible for UK Security Clearance ...

with prompt engineering, RAG architectures, and multimodal models. Contribute to internal tools for monitoring, testing, and improving AI performance. Stay on the edge of ML/AI research — we give you time and resources to explore, learn, and publish. What We’re Looking For 0–3 years of experience … environment. Is curious, ambitious, and eager to build real AI systems that have an impact. What You’ll Get Hands-on mentorship from senior ML engineers, AI researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, Hugging Face, OpenAI ...

is delivered at scale within a modern data environment. Working on a strategic Lakehouse platform built on Databricks, you will influence how production ML models are designed, governed and optimised, helping the business turn complex data into reliable, decision-driving insight. The role combines hands-on engineering with MLOps … governance, access control, monitoring and retraining strategies * Develop automated model validation tests covering unit, integration, regression and bias checks * Translate business problems into effective ML solutions, managing ethical, privacy and data governance considerations * Establish model performance KPIs, reliability measures and production monitoring frameworks * Document model design, assumptions, metrics, risks ...

data and AI Required Skills: Experience in data science, machine learning, or applied analytics Strong proficiency in Python and common ML libraries (pandas, NumPy, scikit‐learn, TensorFlow, PyTorch) Experience designing, training, and evaluating machine‐learning models Solid understanding of statistical methods, predictive modelling, and experimental design … technical stakeholders Experience working in an agile delivery environment Strong problem‐solving skills and attention to detail Desired Skills: Experience with cloud‐based ML services (AWS SageMaker, Azure ML, Databricks) Familiarity with MLOps practices and model lifecycle management Experience with NLP, deep learning, or computer vision Knowledge of data ...

data science, contributing expertise across projects, bids and stakeholder discussions Leading and delivering complex machine learning and AI projects in collaboration with ML engineers, delivery teams and customers Engaging with users to define requirements, scope AI use cases and develop realistic delivery plans Supporting the design, development … tabular data Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC) Understanding of software engineering and ML best practices, including version control, packaging and model deployment Experience training and deploying models using cloud platforms, particularly AWS Ability to communicate complex ideas clearly ...

Data Annotator Analyst – AI/Machine Learning – Expedia Group Location: London (hybrid working) Duration: End of 2026 Pay: £223.18/day About the Role We are looking for a Data Annotator/Data Analyst to support the development and evaluation of AI and machine learning solutions. … consistent, and accurate annotations following defined guidelines Analyze annotated data to identify patterns, issues, and opportunities for improvement Work closely with data scientists and ML engineers to refine annotation strategies Use annotation tools (e.g., Label Studio or similar) to manage and review datasets Perform basic data processing and validation using ...

delivering advanced language and AI solutions to clients. The Role Lead and architect large-scale machine learning projects Build and deploy scalable ML models, pipelines, and systems Mentor engineers and set technical direction across teams Drive innovation through research and adoption of new ML techniques Present technical insights … Machine Learning Engineering or similar senior roles Strong Python skills; experience with deep learning frameworks (TensorFlow, PyTorch) Solid understanding of ML algorithms, statistics, and data modelling Experience with large-scale data tools (Hadoop, Spark, Kafka) Cloud & MLOps experience (AWS, Azure, or GCP) NLP experience highly beneficial Strong ...

Intelligence/Machine Learning applied to cyber security . This is a research-led role , focused on the security of AI/ML systems , exploring emerging threats, developing novel approaches, and shaping future cyber capability. You will work in an environment where problems are genuinely complex and often … have no off-the-shelf solutions . What You'll Be Doing Conducting hands-on AI/ML research in cyber security, with particular focus on the security of AI/ML systems Designing and prototyping innovative solutions to emerging cyber threats Translating research into practical outputs , including prototypes, reports ...

successfully transition into robust, enterprise-grade systems within a modern, cloud-native environment. Responsibilities: Contribute to the evolution of our Data Science platform, defining ML Engineering best practices, tooling and architecture as our team and portfolio grow. Drive automation across the end-to-end data science lifecycle using CI/… infrastructure-as-code to support scalable production workflows. Collaborate across the full model development and deployment lifecycle, spanning traditional ML and generative AI solutions. Work closely with data engineers, software engineers and wider business teams to deliver impactful, production-ready ML services. Write clean, maintainable, high-quality Python code following ...

with large, complex datasets to support AI-driven products and insights 🧠 Assist with feature engineering, model experimentation, and performance optimisation ☁️ Contribute to data and ML pipelines in cloud-based environments 🗄 Work with structured and semi-structured data using SQL 🚀 Support the deployment and monitoring of models in production environments 🤝 Collaborate … years of experience in AI, machine learning, or software/data engineering (including internships, placements, or academic projects) 🐍 Strong Python skills for ML and data processing 🗄 Experience working with SQL and structured datasets ☁️ Familiarity with cloud platforms and modern data stacks 🧠 A solid understanding of machine learning ...

most value. This role combines hands-on technical work with the opportunity to influence strategy, tooling and ways of working , particularly around AI and ML adoption. You’ll be involved across the full lifecycle, from problem definition and experimentation through to deployment, governance and ongoing optimisation. What … data team Collaborating with Product and Engineering on strategic AI-driven initiatives Identifying and developing high-impact use cases for data science and ML Helping define ML lifecycle standards, documentation and governance Communicating insights and model outputs clearly to technical and non-technical stakeholders What we’re looking for Essential ...

Machine Learning Engineer | Early Stage Deep Tech Start Up | London I am partnered with an early stage, London based start up that is building an AI native intelligence layer for private market investing. The platform transforms fragmented documents, deal histories, and proprietary investment data into structured, searchable intelligence … private equity, venture capital, and private credit teams. They are hiring a Founding Machine Learning Engineer to join at early stage, with real ownership over both the core technology and the product direction. This role suits someone with a strong academic background from a leading university , alongside clear ...

responsible for the "factory" that allows our models to live, breathe, and perform in high-pressure production environments across various industries. Key Responsibilities ML Systems Architecture: Design and implement the end-to-end lifecycle of ML models, including automated retraining, model versioning, and monitoring systems. Productionalization: Take validated prototypes from … significant plus. Tooling & Orchestration: Deep experience with containerization (Docker, Kubernetes) and orchestration tools like Kubeflow, Airflow, or Metaflow. Cloud Architecture: Expertise in deploying ML workloads on AWS, GCP, or Azure, utilizing managed services like SageMaker or Vertex AI. Data Foundations: Strong understanding of data modeling, feature stores, and distributed computing ...