Top Machine Learning Jobs in Bristol

Lead design, development, and production deployment of scalable, secure Data & AI solutions on Databricks and Microsoft Foundry. Define AI technical roadmap, mentor an AI engineering squad, partner with stakeholders to prototype and scale use cases, and enforce AI governance, security, and ethical practices.

Lead design, development, and deployment of scalable Data & AI solutions on Databricks and Microsoft Foundry. Define AI technical roadmap, mentor an AI engineering squad, partner with stakeholders to prototype and scale AI products, and ensure governance, security, and ethical AI practices across enterprise platforms.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

The role involves building infrastructure for training open source foundation models, with emphasis on autonomy and contributing in a dynamic team.

The Data Scientist will analyze data, build and refine machine learning models, document technical designs, and collaborate with multidisciplinary teams to deliver AI solutions.

As a P&C Actuary, you will assess insurance risks, review regulatory compliance, support audit teams, and document findings while nurturing client relationships and contributing to practice development efforts.

The role involves designing, building, and deploying ML systems, supporting stakeholders, and operationalizing AI applications in Defence.

Lead engineering systems and teams for an AI chat application, focusing on backend, mobile, and desktop. Oversee strategy, architecture, integration, and high-impact technical decisions for reliable user experiences.

Lead cross-functional teams of machine learning engineers and data scientists, driving technical direction and fostering a collaborative environment to develop high-quality ML-driven capabilities.

The Senior FinCrime Product Owner will design and implement a financial crime prevention product, develop strategy, and lead product delivery at Deblock.

Lead statistical strategy and delivery for Phase I-IV clinical trials embedded with a pharmaceutical sponsor. Design analyses, support protocol and reporting activities, oversee programming/CRO work, apply SAS/R (R Shiny)/Python and ML/DL methods for analyses and automation, and mentor junior statisticians.

Lead assessment, design and delivery of project controls and PMO solutions for major capital programmes. Run workshops, produce findings/recommendations, deploy tools and digital solutions, engage senior stakeholders, support business development, and line-manage staff to drive performance improvements.

Design and lead Oversee's sales enablement strategy, building onboarding, certification, role-based learning, sales methodology, playbooks, and cross-functional engagement. Partner with Product, Marketing, Engineering, and RevOps to enable enterprise sales of AI and automation solutions, measure enablement impact, and improve win rates, ramp time, and sales cycle efficiency.

Lead pricing ML for a real-time energy transaction engine: define mathematical formulation, build and ship production-grade models, optimise pricing and portfolio balance, and communicate model behavior to commercial and engineering stakeholders.

Lead pricing ML for Rosso: define technical direction, build production-grade price-optimisation and probabilistic imbalance models, bridge modelling and MLOps, and communicate model decisions across teams.

Lead a team of product managers to define and execute global AI-driven fraud prevention strategy for New Account Opening. Drive customer discovery, prioritize roadmap, measure portfolio KPIs, partner cross-functionally, analyze ML-driven data, manage product profitability, and support global stakeholders to deliver measurable business outcomes.

Lead the execution of production ML systems: build data pipelines, training workflows, evaluation and inference infrastructure, fine-tune large models (LoRA/QLoRA/SFT/DPO), optimize GPU deployments, and integrate ML into products while ensuring robustness, safety, and reliable user-facing performance.

Lead implementation of production-grade ML systems: data pipelines, training/evaluation workflows, scalable GPU inference, model fine-tuning (LoRA/QLoRA/SFT/DPO), deployment, and monitoring. Collaborate with product and application teams to ship reliable, efficient, and safe ML-powered features for real users while managing latency, cost, and robustness constraints.

Drive new enterprise SaaS business by prospecting, managing, and closing high-value deals. Build territory and account plans, collaborate with Sales Engineering, Marketing, Customer Success and Partners, and sell Conga revenue lifecycle solutions (CPQ, CLM, doc-gen, e-sign). Focus ~90% on new business and consistently exceed quota.

The Staff Machine Learning Engineer will lead the execution of ML systems, ensuring reliability and scalability while collaborating with cross-functional teams to deliver high-quality AI solutions.

As Technical Lead, you'll own ML system execution, manage data pipelines, model deployment, and ensure performance under real-world conditions while collaborating with the team.

Build and validate production-grade ML and AI systems across pricing, underwriting, claims, and portfolio management. Work with structured and unstructured data, LLMs and agentic workflows, extract information from documents, resolve entities, create feature pipelines and inference services, quantify uncertainty, monitor drift, and measure business impact in collaboration with engineers, actuaries, underwriters, and product teams.