1 to 25 of 131 Permanent Machine Learning Jobs in the Thames Valley

models and AI systems. Collaborate extensively with scientific and operational teams to guarantee the robustness, scalability, and reliability of our AI tools. Implementing automation and standardization throughout the ML lifecycle, your efforts will support quicker, data-informed decision-making and boost innovation. Help our CDMO's mission by turning research insights into practical solutions efficiently. Key responsibilities: Compose, construct … successful deployment of machine learning and large language models (LLMs) in practical operational settings, transforming research findings into functional business tools. Facilitate the progress and examination of ML models, involving both standard machine learning and neural network-focused models, as requested by R&D teams. Develop standardized, reusable workflows that can be applied across different projects … on. Key requirements: MSc or BSc in Computer Science, Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning and More ❯

learning models and AI-driven solutions to address business challenges. Collaborate with data scientists to transition prototypes into production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and … validation. Implement model monitoring, versioning, and retraining processes to ensure continuous improvement. Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments. Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation. Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer … lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or More ❯

edge machine learning capabilities. The Role You will join a collaborative Research and Development team based in Oxford, contributing to the development and maintenance of a modern ML operations stack. This includes data acquisition pipelines, data management, and machine learning model training infrastructure. The environment includes both self-managed on premise systems and cloud-based infrastructure … primarily using AWS. You will have the opportunity to influence the technical direction of the ML Ops team, propose new areas for development, and potentially lead your own projects. This is a hybrid role combining remote and on site working. There is no expectation to be available outside core business hours. Key Responsibilities Maintain and improve ML Ops infrastructure Manage … on premise Kubernetes clusters and ML pipelines Integrate ML toolkits into operational workflows Collaborate with ML developers to streamline workflows Suggest and implement technical improvements and new tools Required Skills and Experience Academic background (research Masters level) or industry experience in a relevant field Strong experience managing on premise Kubernetes clusters Deep knowledge of Kubeflow or similar systems such as More ❯

machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure seamless integration of ML models into products. … Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration … with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

AI Engineer at Principal/Staff level to build and to deliver an AI capability. Responsibilities Reporting to VP Engineering Lead design, architecture, and delivery of advanced AI/ML and generative AI solutions, ensuring scalable, secure, and production-ready system. Expert in MCP and RAG patterns Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. … Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow) Hands-on experience with cloud platforms (Azure, AWS) and infrastructure-as-code (Terraform, ECS) Strong background in deploying models via APIs, containers, or cloud-native services Proven track record delivering production-grade AI solutions in complex, data-rich environments Skilled in setting team engineering practices: Git … CI/CD, automated testing for ML code, code reviews, and documentation. Lead tech enablement and mentor engineers, fostering culture of reliability, continuous improvement, and collaboration. Excellent communication skills, able to translate technical strategy into business outcomes and work across team. Minimum 5 years’ professional experience in AI, ML, or applied machine learning engineering roles. Required Skills Expert More ❯

Manage multiple projects from inception to deployment within cloud-based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world … Experience managing multiple end-to-end data science projects across varied data types. Familiarity with DevOps practices and tools like Git. Cloud experience (e.g. Azure, AWS) and working with ML platforms and services. Strong communication skills, capable of explaining complex topics to non-technical stakeholders. Ability to align data science efforts with broader business objectives. Desirable Skills: Experience using R … and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working knowledge of Excel, SQL, Power BI More ❯

the other dedicated to fundamental research that supports both our applications and the broader scientific community. Current areas of interest include large language models (LLMs), optimization methods for deep learning, reinforcement learning (RL), and generative models. Responsibilities:- Contribute to ongoing research in machine learning and artificial intelligence Help develop and implement algorithms Collaborate with researchers and … in preparing publications and technical reports Stay up to date with the latest advancements in AI and related fields Requirement Qualifications Required: Currently enrolled in a PhD program in Machine Learning, Artificial Intelligence, Mathematics, Computer Science, Physics, or a related field Strong interest in research and a background in machine learning or a related area Experience … similar Strong problem-solving skills and ability to work independently and collaboratively Good communication skills and ability to present complex ideas clearly Nice-to-have Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) Previous research publications or submitted papers Why Join Us Gain hands-on More ❯

resilient in our efforts to drive long-term, sustainable innovation to meet humanity's most enduring challenges. We are looking to recruita Research Scientist with expertise in large-scale machine learning. In this role you will design, train, and evaluate advanced machine learning models to support scientific and technological progress across multiple fields Key Responsibilities: Lead significant … results through internal presentations and external publications, as applicable. Maintain high standards of code quality, reproducibility, and team collaboration practices. Qualifications & Experience: PhD or equivalent experience in Computer Science, Machine Learning, or a related discipline. Proven experience in designing and implementing large … scale machine learning systems, including aspects of model training, finetuning, data management, and distributed computing. A record of publications or patents in the field of AI/ML or related areas. Experience in project leadership and mentoring junior team members. Excellent communication skills and the ability to solve complex problems efficiently. Terms of Appointment: You must have the More ❯

Office Based 5 Days Monday – Friday Key skills: Computer Science or A.I qualification or similar, Ideally Python, Machine Learning Concepts, Communication and Evaluation Skills. My Client is the rapidly growing European subsidiary of a global Film company who specialise in lighting, rigging, generators, etc. The also own film studies as well as facilitate studios for other organisations. They … solutions to support operations. You will have the opportunity to gain comprehensive, hands-on experience in multiple areas of a multilocation, commercial business. This role will offer an insightful learning experience in a dynamic and fast-paced work environment. with exposure to real-world applications requiring artificial intelligence and automation. You will work closely with the IT department and … AI deployments. Produce technical documentation, including usage guides and risk assessment templates. Present findings and recommendations to stakeholders through structured viability reports. Recognise personal development needs and proactively seek learning opportunities to support growth in AI and automation. You Will Need To: Currently pursuing or recently completed a qualification in Computer Science, Artificial Intelligence, or a related field Exposure More ❯

be themselves. Position Overview: You will join the Entrust Applied Science team as a research intern. The team consists of 20+ Applied Scientists located in London, UK. We develop machine learning and computer vision models for the Onfido product lines, in particular fraud detection and data extraction on government IDs and biometrics data. You will work together with … a team of scientist who will coach and train you during your internship. We use state-of-the-art technology (deep learning, VLMs), own a large proprietary dataset of images and videos and use a multi-GPU cluster. We use standard frameworks (python, pytorch, tensorflow, dask, AWS). We impact production directly but also the machine learning … and train models on state-of-the-art GPUs Your work will impact products used by dozens of millions of users worldwide You will be mentored by a senior machine learning scientist to make sure you are successful in your mission You will have the opportunity to publish and open-source your work You will be part of More ❯

ML Ops Engineer Remote (Occasional London Meetups) | Full-Time, Permanent | UK Based | Cannot sponsor Specialising in Azure ML, Data Integration & Scalable ML Ops Are you an experienced ML Ops Engineer with a passion for deploying scalable machine learning solutions in Azure? This remote-first role (with occasional meetups in London) offers the opportunity to work on impactful data … collaboration, and continuous learning. Please note: We are unable to offer visa sponsorship for this role. Applicants must have the right to work in the UK. Key Responsibilities Azure ML Operations : Design, deploy, and manage ML models in production using Azure ML . Data Integration : Build and maintain data pipelines using SQL and Azure Data Factory (ADF) . ML Ops … and manage version control using Git . Cross-functional Collaboration : Work closely with actuaries, analysts, and developers to translate data science into actionable insights. Innovation & Support : Stay current with ML trends and support team learning in tools and techniques. What You’ll Bring Essential Experience: Strong hands-on experience with Azure ML or Azure-based production environments. Proficiency in More ❯

help us make this vision a reality. Competitive candidates will have a track record of writing and shipping quality, well-documented and well-tested software in the AI/ML industry. We are looking for candidates with experience in the field of Responsible AI, preferably for generative AI or language applications. In addition to ML engineering and data science skills … leaders will be committed to your career and development from day one. Key Responsibilities Backend development of generative AI evaluations for a Python web application. Integration of AI/ML components with frontend, backend, data and compute infrastructure. Responsible for high quality software implementations according to best practices, including automated test suites and documentation. Participate in code reviews, continuously improving … and product. Liaise with other technical staff and data engineers in the team and across allied teams, to build an end-to-end pipeline consuming other data products. Deliver ML- and data-driven insights on GenAI datasets. Minimum Qualifications A degree in a quantitative or engineering discipline (e.g., computer science, computational biology, bioinformatics, engineering, among others); OR equivalent work experience More ❯

of specific geoscience domains such as stratigraphy, sedimentology, or petroleum geology. Experience of working with subsurface datasets (e.g., wireline, seismic, biostratigraphy). Strong python programming skills and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Excellent communication and teamwork skills in a collaborative R&D environment. AI/ML Implementation: Design and implement AI/ML algorithms to … automate and enhance geological interpretation. Develop AI/ML algorithms to improve geological realism in subsurface models. Validate predictive models using blind test datasets and real-world scenarios. Work closely with colleagues from multiple disciplines to refine and enhance workflows. Stay current with AI/ML and geoscience advancements to drive innovation. Contribute to publications, patents, and technical presentations. Proven … application of AI/ML in geoscience projects. Experience with the energy sector. Familiarity with geological process modelling. Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/orientation, gender identity, age, veteran status, national origin, or any other status protected More ❯

help us make this vision a reality. Competitive candidates will have a track record of writing and shipping quality, well-documented and well-tested software in the AI/ML industry. We are looking for candidates with experience in the field of Responsible AI, preferably for generative AI or language applications. In addition to ML engineering and data science skills … and implement key safety metrics for generative AI (and in particular language) applications. Perform user research to understand the application’s risks and failure modes. Integration of AI/ML components with frontend, backend, data and compute infrastructure Responsible for high quality software implementations according to best practices and expected to participate in code reviews. Liaise with other technical staff … and data engineers in the team and across allied teams, to build an end-to-end pipeline consuming other data products. Deliver ML- and data-driven insights on GenAI datasets. Minimum Qualifications A degree in a quantitative or engineering discipline (e.g., computer science, computational biology, bioinformatics, engineering, among others); OR equivalent work experience as a professional ML engineer or data More ❯

/Chief Scientist (Computer Science & Artificial Intelligence) Employment Type: Full-time/Part-time Key Responsibilities Conduct cutting-edge research and drive applications in areas such as Artificial Intelligence, Machine Learning, Big Data Analytics, Computer Vision, Natural Language Processing, and Intelligent Systems Architecture; Lead the application and execution of national or provincial research projects, and promote the commercialization … one major programming language (Python, Java, C++, Go, etc.) with a solid foundation in data structures and algorithms; In-depth understanding of core algorithms and engineering implementation in AI, Machine Learning, or Computer Vision; Familiarity with large-scale computing platforms, distributed systems, cloud architectures, and related toolchains; Proven experience in translating research into industrial applications. Core Competencies: Strategic More ❯

About the Company We’re working with a next-generation private markets firm that is redefining value creation by combining deep industry expertise with data science and machine learning. This is a unique opportunity to join a company that partners directly with portfolio companies to drive measurable operational and financial performance. They’re now hiring a Lead/Principal … Data Scientist to lead machine learning projects across a wide variety of real-world domains. Working closely with a multidisciplinary team, you’ll have the autonomy to shape technical approaches while staying closely tied to commercial outcomes. This role is ideal for someone who enjoys solving complex, ambiguous business problems using data science, and wants to work at … problems into measurable data science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Act as a technical lead within project teams More ❯

You’ll collaborate with cross-functional teams to design, build, and implement data science solutions that directly feed into core product offerings. This is an exciting opportunity to apply ML and statistical techniques to real-world problems, while also developing in areas such as software engineering, data pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify … opportunities for ML and data science integration Build and maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques to reach accurate conclusions Work with data engineers to ensure clean, usable datasets Contribute … research new methods, and continually build your technical capability What We’re Looking For Proficiency in Python or similar languages for scripting and model building Hands-on experience with machine learning, model deployment, and performance evaluation Strong communication skills – able to simplify complex ideas for various audiences Awareness of Agile methodologies and collaborative software development practices A self More ❯

partners directly with portfolio companies to drive measurable operational and financial performance—powered by data. They’re now hiring a Lead Data Scientist to lead high-impact analytics and machine learning projects across a wide variety of real-world domains. Working closely with a multidisciplinary team, you’ll have the autonomy to shape technical approaches while staying closely … problems into measurable data science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance … design choices Communicate findings and strategic insights to both technical and non-technical stakeholders About You You’re an experienced data scientist with a proven track record of using machine learning to solve real-world business challenges. You’re just as comfortable in Python as you are in a boardroom, and you’re motivated by measurable impact, not More ❯

and driving innovation in the application of our Gen AI platform. We are looking for a professional with a strong grasp of system architecture, particularly in the AI and machine learning domains, who can combine technical insight with a deep understanding of client needs. In this role, you will advise our product teams on design considerations, compliance with … teams during client projects to ensure efficient and secure execution. Key Traits: In-depth knowledge of public cloud platforms (e.g., AWS, Azure, GCP) and their application in AI and machine learning environments. Experience with designing and managing large-scale software systems, including distributed architectures, scaling strategies, and DevOps practices. Familiarity with the full lifecycle of AI model development More ❯

relevant, ensuring ROI and strong performance Champion user trust: Ensure every product decision strengthens trust and reduces friction for legitimate users Leverage data & experimentation: Use analytics, fraud signals, and machine learning models to detect anomalies, test hypotheses, and continuously improve outcomes Monitor performance: Define KPIs for fraud loss rate, false positive reduction, and identity verification success and own … verification, or payments, screening experience a plus Strong grasp of fraud detection systems, identity verification flows, and compliance frameworks (KYC, AML, SCA, GDPR, etc.) Experience working with data science , machine learning , or risk operations teams Analytical mindset comfortable working with dashboards, SQL, or data tools to drive insights Excellent stakeholder management and communication skills; can influence and align More ❯

Software Engineer to meet demand for their products. This role would suit a seasoned PHP Software Engineer who has a strong focus on backend development and ideally knowledge of Machine Learning or LLM. The PHP Software Engineer will work with the R&D team to bring new solutions to life. This role is remote within the UK. To … be a successful, the ideal PHP Software Engineer candidate will have: · A strong career background in PHP and Laravel. · Knowledge of (or an interest in) machine learning and large language models · Experience of working in a small team · Excellent written English skills. What is in it for you? As a talented PHP Software Engineer you can expect: · Great More ❯

Software Engineer to meet demand for their products. This role would suit a seasoned PHP Software Engineer who has a strong focus on backend development and ideally knowledge of Machine Learning or LLM. The PHP Software Engineer will work with the R&D team to bring new solutions to life. This role is remote within the UK. To … be a successful, the ideal PHP Software Engineer candidate will have: · A strong career background in PHP and Laravel. · Knowledge of (or an interest in) machine learning and large language models · Experience of working in a small team · Excellent written English skills. What is in it for you? As a talented PHP Software Engineer you can expect: · Great More ❯

Job Title: AI Engineer Intern (3 or 6 months) - Starting Summer 2026 Project Title: Application of a cell-based machine learning model as a non-linear solver pre-conditioner About SLB: We are a global technology company, driving energy innovation for a balanced planet. At SLB we create amazing technology that unlocks access to energy for the benefit … feeding it into a pre-trained neural network to generate improved initial guesses prior to invoking the non-linear solver. This technique is inspired by the methodology presented in "Learning to Solve Parameterized Single-Cell Problems Offline to Expedite Reservoir Simulation" by Abdul-Akeem Olawoyin and Rami Younis (SPE MS, 2023). Responsibilities The intern will work closely with … for the pre-conditioner This an innovation work, with an opportunity to publish it in a research journal. Qualifications: Studying a Masters in Software development, Artificial Intelligence, Neural Networks, Machine Learning, Numerical methods or a related discipline Python and C++ coding languages, neural-network model and training, numerical methods for solving ODEs and PDEs. SLB is an equal More ❯

experience in Investment Banking environment would be a plus Spanish would be a plus Skills Mandatory Skills : Python, ServiceNow Orchestrator, Azure Cognitive Services, GenAI - LLMOps,RPA - Microsoft Power Automate, Machine Learning - AIOPS, Deep Learning - AIOPS, Reinforcement Learning - AIOPS More ❯