Top Machine Learning Jobs in Bristol

The Senior Product Manager will set product direction, own the development lifecycle, collaborate with teams, and ensure high-quality outputs. This role requires strong opinions on product quality and customer insights.

Lead and own ML platform end-to-end: data/feature pipelines, training and inference infrastructure, model registry, deployment, monitoring, and agentic AI stack. Design integrations across teams and third parties, ensure reproducibility, reliability, cost control, governance and audit trails, and grow a small engineering function supporting data scientists.

Lead product strategy connecting retail operations and accounting for Tekion's ARC platform. Own UK/Canada retail requirements, drive transformation-first customer engagements, define stock management and integration standards, collaborate across product, engineering and implementation, and represent Tekion externally to enable enterprise dealer adoption.

Lead and coordinate cross-functional projects from planning through execution. Improve operational processes using data, budgets, KPIs and AI/automation tools. Create internal communications, manage multiple workstreams, drive stakeholder collaboration, and deliver measurable improvements in team efficiency and culture.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Lead and grow a team of ML scientists to build and productionise credit underwriting, pricing, limits, and lifecycle models. Define Borrowing's ML roadmap for UK growth, new segments, and EU expansion, improve feature engineering and data use, and raise standards for model quality, governance, and iteration speed.

As a Staff/Principal Machine Learning Engineer, you will optimize and scale multimodal inference systems, ensuring high performance and reliability in production environments.

Develop the machine learning compiler stack for Fractile's AI acceleration hardware, ensuring performance of language models through collaboration with hardware and ML engineers.

As a Senior ML Runtime Engineer at Fractile, you will integrate AI acceleration hardware with ML software projects, develop high-performance runtimes, and collaborate on co-design methodologies.

Lead development and productionisation of custom ML and LLM systems for customer feedback: fine-tune and evaluate models, build retrieval/reranking and agentic features, design evaluation frameworks, collaborate with Engineering and Product, mentor team members, and drive model-serving and monitoring work.

As a Machine Learning Engineer, you will develop production-ready ML solutions, collaborate with multidisciplinary teams, and contribute to Defence and National Security challenges.

As a Machine Learning Engineer, you will deploy AI/ML systems, translate client needs into solutions, and engage with users to provide support and improvements.

Design, scale, and productionize ML and physics-based scientific code for drug and materials discovery. Transition prototypes to robust products, orchestrate distributed GPU training, implement hardware optimizations, and support model lifecycle and integration into large-scale simulation frameworks.

Join Starling as a Software Engineer to design, implement, and maintain ML-powered features, collaborating with engineers and data scientists, while delivering impactful solutions in a hybrid working environment.

Recruit experienced mid-to-senior AI/ML engineers and data scientists across the MENA region into a remote talent community offering expert sessions, curated professional development, peer networking, and job-matching opportunities. Members engage in learning, leadership, and collaboration to accelerate careers and access top AI roles.

Build and operate ML infrastructure for training, evaluation, deployment, inference, and experimentation. Improve reliability, scalability, latency, throughput, and cost efficiency. Create reproducible pipelines, observability, benchmarking, and platform tooling enabling researchers and engineers to ship models to production.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.

Design and build end-to-end ML systems for fraud detection: develop and deploy models, create production-ready features and real-time data pipelines, integrate with backend services, and ensure monitoring, security, and observability.

As a Senior Machine Learning Scientist, you'll improve customer outcomes through automated decisioning using ML and statistical modeling, focusing on credit risk modeling and collaborating with cross-functional teams.

Design, develop, deploy, and improve production-grade machine learning and computer vision models. Evaluate model performance, analyze data, support MLOps/CI-CD pipelines, resolve production issues, and mentor junior engineers while collaborating with product and engineering teams to deliver robust, scalable ML solutions.

Research and engineer large multimodal and reinforcement-learning models for robotic agents: design, train, evaluate models; prototype in simulation and on hardware; build data pipelines, simulation environments, and distributed training infrastructure; collaborate to scale promising approaches into production and publish results.

Design and build research prototypes and production-capable systems to enable portable, interoperable agent and model workflows. Develop model routing, provider abstractions, memory and context representations, benchmarking suites, and evaluation protocols. Run ML experiments, implement robust APIs and integration layers, collaborate across research and engineering, and communicate results via reports, demos, publications, and open-source releases.

Lead technical authority for machine learning systems in the Defence domain. Define architectures, functional and non-functional requirements, solve cross-project technical challenges, guide strategy, mentor engineers, and deliver scalable AI solutions for high-stakes clients requiring UK security eligibility and regular on-site presence.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.

As a Lead Machine Learning Engineer, you will set technical direction for ML projects, design scalable systems, mentor engineers, and drive innovation. You'll ensure successful project outcomes while balancing trade-offs and guiding team priorities.