Top Machine Learning Jobs in Bristol

The Research Manager will lead AI-powered insight projects, manage client relationships, oversee team execution, and innovate using AI tools to improve insights delivery.

Lead statistical planning and delivery for clinical studies using R and RShiny, mentor biostatistics staff, prepare SAPs and programming specifications, perform quality control, support submissions and regulatory interactions, and develop/maintain R-based visualization apps and infrastructure.

Develop, train, evaluate, optimize, and deploy machine learning systems from applied research through production, often on edge or embedded hardware. Responsibilities include model development, data pipelines, distributed GPU workloads, evaluation frameworks, MLOps, monitoring, and performance optimization. The role collaborates with software, hardware, systems, and product teams, while offering opportunities to mentor others and guide technical standards. Hybrid work requires at least three days weekly onsite in Bristol, with eligibility for SC clearance.

Lead enterprise sales for Everpure's AI/HPC data infrastructure, driving large deals with F1000 companies. Build executive relationships, lead cross-functional pursuit teams, influence product roadmap, manage a pipeline to exceed revenue targets, and evangelize all-flash storage and data pipeline solutions for AI workloads.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.

The role involves analyzing biological mass spectrometry data, developing software tools, and scaling workflows for AI and human consumption in drug safety assessment.

Lead market pricing for the UK pet insurance book: develop demand, elasticity, and price-optimisation models, monitor competitors and market trends, make rate recommendations, present findings to stakeholders, support pricing strategy, and line-manage one pricing analyst.

Lead end-to-end machine learning systems across data, training, fine-tuning, evaluation, inference, deployment, and monitoring. Build scalable GPU-based infrastructure and reliable production pipelines for large models, optimize performance and cost, and partner with research and application engineering to translate model capabilities into product improvements. Provide hands-on technical leadership, resolve production issues, and ensure measurable, safe, and maintainable ML iterations.

Industry Expert who sets the technical bar for advanced AI, ML, systems, or forward-deployed engineering programs. Responsibilities include reviewing deployed projects, leading technical defenses and mock review boards, delivering occasional live sessions, critiquing architecture and tradeoffs, and advising instructors on difficult design decisions. The role requires production-scale engineering experience, senior-level judgment, a public technical footprint, strong English, and comfort with AI tools. It is fully remote and requires approximately 4–10 hours monthly.

Lead identification, development, and global deployment of AI and automation solutions to optimize forms and precedents content operations. Prioritize opportunities, collaborate with cross-functional teams, ensure governance and quality, integrate solutions, report outcomes to leadership, and drive continuous improvement and responsible AI practices.

As a Lead Data Scientist, you will set technical direction, ensure project delivery, manage client relationships, and mentor data scientists.

The Computer Vision Engineer will lead AI initiatives in the defense sector, delivering solutions and mentoring teams while driving technical strategy and capability development.

Create clear, customer-focused documentation and help content for cloud-based video security, access control, and intrusion platforms. Design user-centric guides, peer-review content for quality and consistency, and collaborate with Engineering, Support, Escalations, and UX teams to improve documentation and product usability.

Lead commercial expansion into the UK Air domain, owning sales, pipeline, bids, contracts and account growth. Build senior customer and partner relationships, translate AI/ML capability into operational outcomes, and ensure solutions are deliverable and strategically aligned while working with multidisciplinary teams in secure defence contexts.

Own commercial strategy and operations for enterprise pharma and AI accounts: drive pilots-to-revenue, account expansion, pipeline management, pricing, forecasting, and deal strategy. Build cross-functional relationships, push deals through legal/procurement/IT, act as CEO counterpart to shape strategy and product roadmap, and be highly present in person with customers and at conferences.

Lead end-to-end research applying advanced ML/DL (transformers, GNNs, RL, ensembles) to generate alpha across digital asset markets, build production-grade pipelines, prevent leakage/overfitting, analyze microstructure and on-chain data, and mentor junior researchers.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

Lead ML strategy and delivery for Workforce Management: forecasting, routing, assignment, escalation and time-to-completion prediction. Build, ship and maintain production ML systems, coach and grow a team of ML scientists, work cross-functionally to turn operational problems into pragmatic ML solutions, and improve customer and operational outcomes.

Lead Vegetation Intelligence product, owning roadmap from ML detection models to customer-facing risk products. Advance detection models, integrate outputs into outage and ignition risk, run user research, and translate model capability into actionable B2B products used in the field.

Identify, qualify, and nurture enterprise leads for Cohere's AI solutions through outbound outreach, BANT qualification, Salesforce pipeline management, and collaboration with marketing. Run smaller sales cycles to close opportunities and stay current on industry and product trends.

Lead data visualisation and reporting strategy: design interactive dashboards, standardise metrics, modernise executive reporting, embed visualisations into SaaS products, develop data storytelling frameworks, translate complex analytics into actionable narratives, and train teams to drive insight adoption across the organisation.

As a P&C Actuary, you will assess risks for insurers, support audit teams, and maintain compliance with regulations, while growing client relationships and improving tools for efficiency.

Own and grow the EMEA territory by building pipeline, managing full sales cycles, closing enterprise travel-tech deals, and developing partnerships with TMCs and travel providers. Represent the company at events, engage senior executives, and share market feedback with Product and Leadership to drive strategic outcomes.

The Senior Machine Learning Engineer will design and implement ML pipelines, optimize LLM performance, and collaborate on AI infrastructure for cost-efficient solutions.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.