201 to 225 of 238 Machine Learning Jobs in the Thames Valley

an established and rapidly growing Technology company who are looking for a technical Product Owner to join them on a permanent basis They have created an advanced AI/ML data platform that integrates into Casino and Sports betting brands. It is a search and comparison engine that can help users to make better choices and informed decisions. In this More ❯

job, it’s a chance to shape the direction of the due diligence industry with our market-leading product. Whether you’re in engineering, data science, product, AI/ML or infrastructure, you’ll be solving hard, high-impact problems: scaling distributed systems to fuel explosive growth, making sense of multilingual and unstructured data, applying AI/ML to real … and cost-efficiency. You won’t just be shipping features, you’ll be shaping architecture, tooling, models, and pushing the boundaries of what’s possible. For people who love learning The Challenge Our product is experiencing tremendous demand, presenting us with the exciting challenge of scaling our platform and technology. We need to deliver accurate insights while doubling down … top condition. Life Insurance – let's hope nobody ever needs this! Unlimited holidays – yes, it really is uncapped – take the time you need, when you need it. Everyone is learning, developing and challenging themselves – so we have a £1k professional development fund per year if you want to learn new skills, even new things outside of work. Most importantly More ❯

oversee preprocessing, cleaning, and curation workflows essential for efficient LLM training and inference. Model Development & Evaluation Lead the development and evaluation of LLMs, leveraging expertise in transformers , self-supervised learning , and large-scale distributed training . Optimize training pipelines for enhanced performance, compute efficiency, and responsible AI alignment. LLM Deployment … Scalability Manage the end-to-end deployment of LLMs and foundation models in production environments, focusing on system integration, inference, and optimization. Cross-functional Collaboration Engage with research scientists, ML engineers, and product teams to align technical advances with business needs. Mentor junior researchers and engineers, promoting best practices in LLM development, scalable model deployment, and evaluation processes. Required Skills … Qualifications Experience: 3+ years in NLP, transformer models, deep learning, and scalable AI pipelines, with demonstrated involvement in LLM development, fine-tuning, or deployment. Technical Skills: Proficiency in Python and frameworks such as PyTorch , TensorFlow , or JAX . Strong familiarity with distributed computing and data engineering tools (e.g., SLURM , Apache Spark , Airflow ). Hands-on experience with LLM training More ❯

Presales, Solutions Consulting, or Technical Architecture. Experience in AI-enabled customer experience transformation. Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan … Cycle-to-work scheme 28 days paid annual leave (including company-wide wellbeing days) Access to LinkedIn Learning and ongoing development programs If you’re ready to shape the future of AI-driven customer experience and thrive in a collaborative, fast-paced environment — we’d love to hear from you. More ❯

Write clean, testable, and maintainable code. ->Collaborate in an agile environment, participating in sprint planning, code reviews, and team knowledge-sharing sessions. Tech Stack ->TypeScript ->Next.js ->Node.js ->GCP ->AWS (ML) ->CI/CD with GitHub actions and workflows ->SQL (PostgreSQL, MySQL) ->NoSQL (MongoDB, Firestore, Redis) ->RESTful APIs - GraphQL Requirements for Tech For Good (Audio Intelligence) | Innovative Products | Mid-Level (Back … who can balance delivering features with maintaining code quality. ->Strong communication skills and ability to collaborate across teams. Nice to haves... ->Python experience. ->GCP experience. ->Experience with AI/ML-powered applications. ->Exposure to real-time data processing. ->Knowledge of CI/CD pipelines and automated testing. Remuneration & Benefits £50K - £65k + Equity (once probation is passed) 40 days holiday More ❯

will collaborate with design and user research to gather feedback, ensuring our platform meets both technical and user needs. If you are passionate about building next-generation AI/ML products, thrive in a fast-paced Agile environment, and excel at collaborating with engineers to solve complex problems, then this role is for you. Responsibilities Work closely with software engineering … experience as a software engineer, SRE/DevOps engineer, or similar technical role is highly valued and will help deeply engage with the engineering team. Familiarity with AI/ML infrastructure or HPC (high-performance computing) environments. Understanding of GPU computing, cloud computing services, or data centre operations is a plus. Experience working at a startup or in a rapidly More ❯

Staff Software Engineer – AI/ML (Business Systems Intelligence) London (Hybrid – 2 days per week in office) An opportunity to take on a high-impact, hands-on leadership role within a scaling global SaaS company that’s using AI to reinvent how internal business systems and data work together. As a Staff Software Engineer (AI/ML) , you’ll be … mentor other engineers, and help define how AI and automation are adopted across the company. What You’ll Do Lead the design, architecture, and implementation of internal AI/ML systems for business intelligence. Build robust APIs, microservices, and data pipelines to power intelligent, data-driven tools. Develop retrieval-augmented generation (RAG) systems using vector databases for contextual AI. Set … backend or full-stack engineering, ideally within a SaaS or data-driven business. Strong knowledge of LLMs , prompt engineering, and fine-tuning approaches. Hands-on experience with AI/ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and More ❯

evolve the product vision for AI-powered clinical operations platforms, with a focus in agentic automation of workflows. Cross-Functional Leadership: Lead cross-fuanctional pods composed of AI scientists, ML engineers, software developer engineers, and UI/UX researchers. Drive execution through agile methodologies, ensuring delivery of scalable, secure, and compliant AI solutions. Stakeholder Engagement: Collaborate with clinical SMEs, regulatory … a fast-paced tech or life sciences environment Deep understanding of the clinical trial lifecycle and operations (e.g., clinical operations, site monitoring). Strong technical fluency in AI/ML concepts, including, LLMs, prompt engineering, and agent orchestration Demonstrated ability to lead cross-functional teams and deliver products in regulated envioronments Excellend communication and stakeholder management skills Bonus Points: Advanced … degree in life sciences, computer science, or a related field Experience with Agentic AI frameworks and tools (e.g., LangGraph, CrewAI, AutoGen) Familiarity with cloud native-AI infrastructure (e.g., Azure ML, AWS Bedrock, Snowflake) Prior experience in building AI products for clinical development or healthcare analytics RDSITAI IQVIA is a leading global provider of clinical research services, commercial insights, and healthcare More ❯

high-speed visual search and reasoning Manage cloud infrastructure (compute, networking, storage, security, observability) Set up CI/CD pipelines for fast, reliable deployments Deploy and integrate AI/ML models into production pipelines Take a product-first approach: asking “why,” not just “how” What You’ll Need Essential Skills Startup Mindset: Bias for action, ownership, comfort with ambiguity Backend … + strong data modeling Containers: Docker; orchestration tools Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. More ❯

Do you want to own the ML infrastructure at a frontier AI startup? Have you built cloud and ML systems from scratch, not just maintained them? Are you ready to shape the backbone of 3D generative AI? SpAItial is pioneering the development of a frontier 3D foundation model , combining cutting-edge AI, computer vision, and spatial computing to redefine how … seed funding , with half allocated to compute, SpAItial is a 10-person research-focused team moving fast towards a public demo later this year. We’re looking for a ML & Cloud Infrastructure Engineer to take ownership of our entire ML infrastructure. This isn’t a ticket-handling MLOps role — it’s a chance to build the systems that will power … frontier AI research and production at scale. Key Responsibilities: Design and deploy scalable, high-performance cloud infra for ML workloads Build and manage GPU clusters, storage systems, and distributed training environments Set up and optimise containerised workflows (Docker, Kubernetes, Terraform) Implement robust monitoring, incident response, and CI/CD practices Collaborate closely with researchers to integrate and scale experiments This More ❯

engineers to define data specifications, support experimentation, and integrate active learning loops that improve AI models over time. REQUIREMENTS 2 years of proven experience in data engineering for ML/AI, with strong proficiency in Python, SQL, and distributed data processing (e.g., PySpark). Hands-on experience with cloud data platforms (GCP, AWS, or Azure), orchestration frameworks (e.g., Airflow … collaborating with creative, technical, and legal teams. NICE TO HAVE Experience with Blender scripting, photogrammetry, or NeRF dataset prep. Familiarity with Unity or Unreal Engine pipelines. Understanding of active learning or data augmentation for AI. WHAT THEY OFFER: Hybrid work - 3 days/week from the office Employment contract in the UK Pension program, health and life insurance More ❯

client outcomes. Key Skills & Experience Essential: Proven experience as a Product Manager for data-driven enterprise products. Strong understanding of data architecture, analytics, and governance. Experience integrating AI/ML models, LLMs, or agent-based systems into commercial products. Familiarity with Model Context Protocol (MCP) or similar AI orchestration frameworks. Ability to translate complex technology into clear business outcomes and … collaboration, and stakeholder management skills. Proficiency in Agile methodologies and tools (Jira, Confluence). Desirable: Knowledge of cloud data technologies (SQL, NoSQL, data lakes). Experience with AI/ML frameworks and orchestration tools. Background in financial services or other regulated industries. Understanding of data processing and reconciliation solutions. What’s on Offer Competitive salary + excellent benefits package Hybrid More ❯

developers to test, benchmark, and deploy GPU-accelerated software and AI models at scale. Responsibilities: Design and maintain CI/CD pipelines for GPU-accelerated codecs and AI/ML libraries. Automate performance benchmarking and regression testing across multiple GPUs and hardware targets. Manage containerised environments (Docker, Kubernetes) to deploy GPU and ML workloads at scale. Provision and optimise GPU … cloud infrastructure (AWS, GCP, Azure) using Terraform/Ansible. Collaborate with GPU engineers and researchers to integrate CUDA, SYCL, Vulkan, and ML kernels into production workflows. Support secure packaging, deployment, and distribution of GPU-accelerated software to partners and clients. Evolve infrastructure to support hybrid AI/codec workflows, including ML inference and neural compression pipelines. Requirements: Hands-on experience … OpenCL) or HPC performance optimisation. Strong scripting and programming skills (Python, Bash, C/C++ exposure a plus). Knowledge of monitoring, logging, and performance testing for GPU/ML workloads. Excellent collaboration skills — able to work with research, engineering, and product teams. Desirables: Experience in MLOps/LLMOps (MLflow, Kubeflow, Weights & Biases, experiment tracking). Exposure to video processing More ❯

to the CMO (also CIO/CPO), lead a small DS team, and work cross-functionally with product, tech, innovation, and local business units. Responsibilities Set the AI/ML roadmap Lead model development (personalisation, churn, pricing) Scale internal GenAI tools across markets Ensure compliance (GDPR, EU AI Act) Influence senior stakeholders incl. CMO, CTO, CEO Requirements 10+ years in … ML/DS, including senior leadership Hands-on background in model deployment Strong B2C experience (e.g. ecommerce, gaming, telco) MSc required; PhD optional Executive-level stakeholder management Exposure to GenAI and cloud ML stacks (Databricks, Azure, AWS) Pathway to Chief Data Officer Interested? Please apply below. More ❯

Do you want to design and lead AI strategy across a PE portfolio? Have you built and delivered AI/ML systems that directly impacted business outcomes? Are you ready to work with board-level leaders to define how AI transforms financial services? A specialist private equity firm is hiring a Principal or Director of Data & AI to lead strategic … deliver AI & data strategies across portfolio companies and internal teams Lead technical diligence on AI-readiness and opportunities during deal evaluation Build and deploy reusable LLM/AI/ML systems (agents, copilots, etc.) to unlock value Define governance frameworks across risk, explainability, audit, and compliance Own internal AI transformation—deploying tools, platforms, and training programmes Build and manage a More ❯

Security Architect – ML/AI Systems 📍 UK | Hybrid | Up to £130,000 + Package | SC Eligible We’re looking for a hands-on Security Architect with deep expertise in ML/AI systems to join a leading Security Team. This is a rare opportunity to act as a technical SME, shaping the security of AI-driven systems in high-stakes … environments. What you’ll be doing: Own and design security architectures for ML/AI systems, ensuring robust protection across all stages of the AI lifecycle. Act as the technical SME, providing guidance and solutions to complex security challenges in AI/ML deployments. Work closely with engineering, data science, and DevSecOps teams to embed security best practices. Assess and … mitigate risks specific to AI models, data pipelines, and ML/AI frameworks. Influence security strategy and contribute to cutting-edge AI security initiatives. Experience & Skills Required: Proven hands-on experience securing ML/AI systems (not theoretical knowledge). Deep technical expertise in AI/ML architectures, data pipelines, and model lifecycle security. Strong understanding of threat modeling, risk More ❯

Suite, Axure, and interactive prototyping. A portfolio showing beautiful, functional, user-focused designs. A visionary yet pragmatic approach, with sharp attention to detail. Bonus points if you’ve designed machine learning-driven products, worked with design systems, or have a knack for microcopy. More ❯

curious and resilient in our efforts to drive long-term, sustainable innovation to meet humanity's most enduring challenges. EIT is seeking a Product Manager to join the Applied ML team at Ellison Institute of Technology, as we set up our Data Science and Engineering organization and begin the journey of enabling various programmes and opportunities within EIT through the … disparate technical and domain expertise to a single purpose/vision This person would interface directly with our Product Leadership, as well as number of technical (e.g., Data Science, ML Ops), business and operational leads (within the programmes) and own the product strategy, feature definition, and development timelines for products that support programme or Applied ML objectives. Key Responsibilities: Define … and shepherd holistic Applied AI/ML product strategy and delivery in alignment with broader programme, business or research priorities including: Working with programme business leads to identify opportunities for applied AI/ML product and set the product vision and strategy in alignment with the programme mission Act as a link between technical team (e.g., data scientists, data engineers More ❯

office 3 days a week. You will help build and manage the robust data infrastructure that powers their AI-driven analysis platform and allows them to train their foundational ML models. You will work closely with both the ML team and the product team, managing huge datasets of binary analyses and ensuring that the data requirements of both teams are … to have: Experience working with modern cloud data warehouses like Snowflake or BigQuery. Experience working with vector databases (e.g. Qdrant) Experience/understanding of data requirements for large-scale ML training. Experience working in a fast-paced start-up environment. Some domain knowledge/interest - knowledge of compiled languages (C/C Rust etc), binary analysis. Unfortunately, this firm are More ❯

possible in 3D content creation. What you’ll do Build and scale backend services and APIs for web and desktop applications. Design and implement distributed systems for async processing, ML workflows, and asset pipelines. Own authentication, billing, and subscription systems — ensuring reliability and seamless user experience. Drive observability, performance tuning, and deployment automation across the stack. Collaborate closely with product … frontend, and ML teams to deliver features that delight and scale. You should have 5+ years of experience developing production-grade backend systems and APIs. Strong skills in Python (FastAPI or similar) and modern cloud infrastructure. Deep understanding of system design, scalability, and reliability . A product-oriented mindset — you design with end users and UX impact in mind. Passion … interfaces. Nice-to-haves Experience with cloud-native infrastructure (AWS, GCP, or Azure). Familiarity with auth, billing, or subscription systems . Background in 3D graphics, creative tooling, or ML pipelines . Knowledge of observability tools like Grafana, Prometheus, or OpenTelemetry. This is a rare opportunity to join an early-stage team backed by leading deep-tech investors, building the More ❯

stakeholders to test bold ideas quickly and effectively Translate insights into concept pitches, MVPs and business cases for internal buy-in Champion a culture of curiosity, experimentation, and continuous learning Track and share learnings across the company to inform product and strategy decisions Build and evolve lean frameworks for innovation processes, including discovery and validation Skills and Experience 6+ … to move ideas from an idea or concept, to MVP Passion for future trends, emerging tech, and spotting what's next before its obvious An understanding of AI/ML fundamentals, including supervised & unsupervised learning, LLMs, generative models, etc. Demonstrable data literacy skills, ability to manipulate and interpret datasets unaided, including experiment results Strong technical grounding, able to comfortably More ❯

AI Scientist ~x3 Job Openings Location: Oxford Working Model: Onsite every Tuesday & Wednesday About the Company The Applied AI team sits within cience and engineering division, focused on translating ML research into real-world impact across healthcare, climate, and biotechnology. Their current projects include antimicrobial resistance (AMR), plant phenotyping, and patient-journey modelling. About the Roles & Responsibilities Protein & DNA Modelling … building and adapting ML models to biological sequence and structure data, often leveraging foundation models such as ESM and EMO. Computer Vision & 3D Reconstruction – developing applied AI solutions for imaging data, including phenotyping, microscopy, and sensor-based reconstruction systems. LLM Engineering for Autonomous Labs – designing and deploying large language models to automate experimental workflows and scientific protocols. Qualifications PhD in More ❯

AI Scientist ~x3 Job Openings Location: Oxford Working Model: Onsite every Tuesday & Wednesday About the Company The Applied AI team sits within cience and engineering division, focused on translating ML research into real-world impact across healthcare, climate, and biotechnology. Their current projects include antimicrobial resistance (AMR), plant phenotyping, and patient-journey modelling. About the Roles & Responsibilities Protein & DNA Modelling … building and adapting ML models to biological sequence and structure data, often leveraging foundation models such as ESM and EMO. Computer Vision & 3D Reconstruction – developing applied AI solutions for imaging data, including phenotyping, microscopy, and sensor-based reconstruction systems. LLM Engineering for Autonomous Labs – designing and deploying large language models to automate experimental workflows and scientific protocols. Qualifications PhD in More ❯

museums to digitise previously unobtainable assets at scale. This gives us one of the most unique and physically accurate 3D datasets in the world. Now we’re building an ML-powered pipeline that can automatically predict material properties (diffuse, roughness, specular, metallic, normals) from photogrammetry input alone - without flash. This is made possible by tapping into our uniquely rich dataset … our web SaaS platform, enabling new 3D-PBR asset creation workflows. Work with frontend developers to design and implement high-performance APIs that deliver exceptional user experiences. Integrate with ML infrastructure to orchestrate model workflows, manage job queues, and deliver results to users. This is a high-impact role for someone that loves to define and bring completely new technologies … and subscription management (Stripe) Design and manage user databases and data models (MongoDB, PostgreSQL) Implement asset storage, retrieval, and management systems (AWS S3) Build job queue management for async ML workflows (SNS, SQS) Setup application monitoring and logging (CloudWatch, Grafana, Prometheus) Implement CI/CD for application deployment (Bitbucket Pipelines) Create API documentation and developer tools What we are looking More ❯

sit at the intersection of customer success, analytics, and engineering , ensuring every client deployment performs at its best. You’ll act as the technical bridge between customers, product, and ML engineering , leading post-install optimisation, investigating data-driven performance issues, and scaling best practices across a growing customer base. You’ll also manage 1 x Technical Account Manager , shaping how … consistently delivering excellence. Your Background 8–12 years in Technical Account Management , Customer Engineering , or Solution Delivery for AI, IoT, or enterprise SaaS platforms. Strong understanding of edge AI, ML pipelines, or computer vision systems (e.g., PoS, SCOs, IoT). Experience working with monitoring frameworks (Grafana, Datadog) and analysing technical performance data. Proven track record in building relationships with enterprise More ❯