1 to 25 of 436 Remote/Hybrid Machine Learning Jobs in England

fantastic opportunity for a Senior Machine Learning Scientist to work for a health-tech software company developing advanced machine learning models used within clinical research. The organisation applies modern machine learning techniques to complex medical datasets to support better understanding of patient outcomes … Scientist/Machine Learning Researcher/AI Research Scientist/Computer Vision Scientist/Deep Learning Scientist/AI Scientist/ML Research Engineer/Python/PyTorch/Deep Learning/Computer Vision/3D Imaging/Volumetric Imaging/Self-Supervised Learning/ ...

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 ...

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 ...

Machine Learning Engineer/Junior Machine Learning Engineer Level: Junior ML Engineer (£56,000) | ML Engineer (£65,000) Location: London About the Role Our client is a global defence, security, and intelligence consultancy delivering high-assurance digital, cyber, and AI solutions into some … wider government environments. The work spans exploratory research, rapid prototyping, and full production deployment. You will be solving complex, real-world problems using modern ML and LLM techniques, working on sensitive, high-impact systems where quality, governance, and operational readiness genuinely matter. What You’ll Be Doing Designing and developing ...

Learning Engineer (Python AWS MLOps) Remote UK to £90k Are you a tech savvy Machine Learning 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 … Learning Engineer with advanced Python coding skills and a strong knowledge of AWS 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 good knowledge ...

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. ...

, and operations research (linear, mixed integer programming, heuristics) Fluent in Python(required) and other programming languages (preferred)with strong skills in applying DS, ML, and OR packages (scikit-learn, pandas, numpy, gurobietc.) to solve real-life problems and visualise the outcomes (e.g. seaborn) Proficient in working with cloud platforms … preferred), code versioning (Git), experiment tracking (e.g. MLflow) Experience with cloud-based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/Dagster) and containerised solutions (e.g. Docker, ECS) nice to have Experience in code testing (unit, integration ...

, and operations research (linear, mixed integer programming, heuristics) Fluent in Python(required) and other programming languages (preferred)with strong skills in applying DS, ML, and OR packages (scikit-learn, pandas, numpy, gurobietc.) to solve real-life problems and visualise the outcomes (e.g. seaborn) Proficient in working with cloud platforms … preferred), code versioning (Git), experiment tracking (e.g. MLflow) Experience with cloud-based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/Dagster) and containerised solutions (e.g. Docker, ECS) nice to have Experience in code testing (unit, integration ...

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 ...

across several workstreams using rule-based methods, supervised and unsupervised learning, forecasting, and optimisation techniques. Work closely with product owners, data engineers, and ML engineers to deliver high-quality, scalable ML solutions. Prepare, clean, and engineer datasets for training and validating machine learning models. Define and implement … performance metrics, including both ML performance and computing resource usage (CPU/memory). Support end-to-end deployment of machine learning models, including monitoring, retraining pipelines, and lifecycle management. Leverage third-party and syndicated data to generate insights relating to trade promotions, pricing, distribution, and digital shelving ...

+ £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 ...

Science, Data Science, Statistics, Engineering, or equivalent. Proficiency in Python, SQL, ETL, APIs, and cloud platforms (AWS/Azure/GCP). Knowledge of ML algorithms, operationalisation, and model monitoring. Strong understanding of governance, security, and ethical frameworks in health data. Excellent communication, influencing, and negotiation skills. Experience delivering complex … projects and mentoring others. Desirable Postgraduate qualification (MSc/PhD) in data science, ML, or related subject. Experience with health data standards (HL7, FHIR, SNOMED). Familiarity with NHS datasets and national initiatives. Experience with BI tools such as Power BI, Tableau, or Looker. Research track record with academic ...

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 ...

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 … 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 ...

Applied Science PhD Intern, you will work on cutting-edge challenges in large language models (LLMs), graph-based retrieval, personalization, and scalable machine learning systems. You'll collaborate closely with experienced scientists and engineers to bring innovative research ideas to life through real-world prototypes and high-impact … algorithms at scale Excellent communication skills, with the ability to explain complex concepts clearly. Preferred Qualifications: Publication record in top-tier AI/ML/NLP conferences or journals. experience working with: Large Language Models Transformer architectures Evaluation and optimisation of LLM-based systems Key Skills Large Language Models ...

developing data-efficient machine learning solutions for complex engineering and optimisation problems. This is an opportunity to join a highly research-driven ML lab, working on probabilistic modelling, Bayesian optimisation and decision-making methods, with a strong emphasis on theoretical rigour and real-world impact. The team regularly … publishes at top-tier machine learning conferences and contributes to open-source ML libraries. The Role You'll conduct original research in areas such as probabilistic models, active learning and Bayesian optimisation, while collaborating closely with other researchers and applied teams. The role blends academic-quality research ...

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 ...

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 ...

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 ...