Top Machine Learning Jobs in Bristol

Supports technical sales for HPC and AI solutions by gathering customer requirements, designing architectures, preparing proposals, delivering demonstrations and proof-of-concepts, and validating solutions. Collaborates with sales teams, customers, partners, and technical specialists to position solutions, manage opportunities, contribute to pipeline growth, and support successful knowledge transfer. The role also involves tracking emerging technologies, participating in forecasts, documenting activities, and developing expertise in enterprise infrastructure and cloud technologies.

Conduct empirical AI safety research with mentor guidance, owning projects from hypotheses and controlled experiments through analysis and technical writing. Build and debug evaluation harnesses, agent environments, datasets, monitoring methods, and post-training experiments. Investigate model failures, alignment, deception, misuse, multi-agent risks, and evaluation reliability. Produce reproducible code, experiment logs, research analyses, and papers for potential submission to leading machine learning conferences.

Leads the EMEA and LATAM Advanced Services architecture delivery team, overseeing complex customer and partner projects across pre-sales and delivery. Responsibilities include recruiting and developing architects, collaborating with Sales, Product Management, Engineering, and Customer Experience, presenting enterprise solutions, managing escalations, ensuring customer satisfaction, and shaping the services portfolio. The role requires strategic services expertise, strong leadership, data-platform knowledge, executive communication, and the ability to travel extensively across the region.

Independently assess medical device software lifecycle processes and technical documentation under EU MDR, UK MDR, IEC standards, and related cybersecurity guidance. Review SaMD and AI-enabled devices, raise and resolve technical findings with manufacturers, interpret regulatory requirements, and deliver consistent assessments using established workflows with minimal oversight.

Support UK insurance pricing through price modeling, implementation, strategy, monitoring, and development of new products. The role balances pricing accuracy, profitability, and price-comparison competitiveness while collaborating with data scientists, product, and underwriting teams. It also involves developing pricing capabilities using actuarial methods, predictive modeling, machine learning, and AI, while continuing actuarial education and monitoring regulatory changes.

Lead project controls and performance consulting engagements for major capital projects and programmes. Assess client environments, develop recommendations, deliver workshops, tailor methodologies, support digital solutions, prepare reports, contribute to bids and business development, and manage direct reports. The role requires project controls expertise across scheduling, cost, risk, change, performance reporting, PMO environments, stakeholder engagement, and infrastructure or defence programmes.

Leads AML transaction-monitoring optimization, rule testing, threshold tuning, scenario design, and false-positive reduction. Drives FIU automation and workflow improvements, evaluates AI and LLM tools, supports alert triage and investigations, and partners with Product, Engineering, Operations, and vendors on compliance technology integrations. Helps scale monitoring frameworks across products, jurisdictions, and transaction volumes while maintaining regulatory alignment.

Leads biostatistical activities for Phase II–III clinical trials, from protocol design through reporting and regulatory submission support. Responsibilities include statistical analysis planning, sample size calculations, SAP development, TLF review, database lock support, safety reporting, regulatory responses, and oversight of programming or CRO work. Collaborates with cross-functional clinical teams and uses SAS or R for analyses, modeling, simulation, exploratory work, and quality control. Coordinates statistical activities across studies and applies advanced statistical and machine learning methods.

Drive partner-led CCaaS growth across EMEA and APAC by recruiting, onboarding, and scaling strategic partners. Lead co-selling motions, commercial opportunities, partner enablement, packaged offerings, forecasting, and performance reviews. Translate Zendesk AI and contact center capabilities into partner use cases and revenue opportunities while collaborating with Sales, Marketing, Product, Engineering, Solutions Consulting, and Customer Success teams.

Develop, debug, test, and optimize machine learning models, training pipelines, inference systems, numerical methods, and supporting infrastructure. Build reproducible Python workflows, diagnose computational issues, validate implementations, use coding agents, and document technical findings. This remote role requires approximately 15 hours per week and rapid task availability.

Evaluate AI model outputs on data science, statistics, machine learning, experimentation, and quantitative problems. Develop expert prompts, datasets, and reference solutions; identify statistical and methodological errors; and provide structured feedback to improve model performance. The role requires Python, machine learning, statistics, data analysis, experimentation, Pandas, and data modeling skills.

Design and deliver enterprise-grade machine learning systems and AI-powered applications for banking. Build scalable, secure, distributed applications and automated cloud, desktop, and ML pipelines. Apply MLOps practices for versioning, reproducibility, and observability while collaborating with cloud and site reliability engineering teams. Develop reusable libraries and business-critical, data-intensive solutions, aligning machine learning problems with business objectives. The role may include mentoring or people leadership.

Serves as a customer-facing fraud and identity subject matter expert across pre-sales, onboarding, and expansion. Advises enterprise customers on risk profiles, fraud strategies, identity workflows, integrations, regulatory hurdles, and implementation best practices. Leads onboarding and go-live readiness, coordinates cross-functional teams, validates milestones, and helps customers optimize verification workflows, reduce friction, accelerate deployment, and maximize product value.

Lead a small team developing secure, reliable agentic AI capabilities. Responsibilities include setting technical direction, building agent monitoring, evaluation, and guardrail frameworks, performing machine learning tasks, translating research into production features, mentoring engineers, and contributing hands-on code and technical designs. The role focuses on agent collaboration, trust, security, quality measurement, and scalable software delivery.

Leads global AI-first MarTech engineering strategy, architecture, governance, compliance, and delivery. Oversees scalable digital platforms, public-facing properties, GenAI applications, R&D, proof-of-concepts, and automated compliance capabilities. Builds and mentors a global team of engineering and AI professionals, manages vendors, and partners with marketing, business, cloud, security, privacy, infrastructure, and legal stakeholders to deliver secure, high-performance digital experiences.

Leads end-to-end AI-powered insight and market research programmes for major client accounts. Responsibilities include shaping briefs, advising clients, managing scopes, budgets, timelines and resources, supporting pitches, leading consultants, and improving research delivery through AI-enabled tools. The role requires commercial research expertise, strong client leadership, organizational skills, and curiosity about emerging AI technologies.

Own the vision, strategy, roadmap, integration, commercialization, and executive stewardship of Kaltura’s new AI-powered learning and enablement platform. Lead 0-to-1 MVP delivery and post-MVP expansion across AI course generation, conversational tutoring, multimodal learning, simulations, and personalized journeys. Partner with engineering and GTM teams on architecture, pricing, packaging, positioning, enterprise sales, and integration of acquired products.

Develop and optimise state-of-the-art machine learning models for specialised hardware and systems containing thousands of accelerators. Responsibilities include model training, benchmarking, profiling, kernel optimisation, experiment design, software testing, code reviews, and collaboration with research, software, and product teams to advance AI hardware and software. The role also involves distributed training and inference, performance analysis, and engagement with the broader AI community.

Leads technical direction for GitLab’s Core DevOps services, covering CI, CD, planning, and source control. Defines architecture, quality metrics, migration strategies, and technical roadmaps; addresses systemic risk and complex design decisions; prototypes and writes code when needed; partners with Infrastructure, Security, SRE, and Product; adopts AI capabilities; mentors senior engineers; supports incident response and senior technical hiring.

Provides statistical leadership for Medical Affairs, real-world evidence, comparative effectiveness, HTA, and HEOR activities. Designs and analyzes observational, clinical, Phase IV, and indirect treatment comparison studies; evaluates data quality, bias, uncertainty, and applicability; supports evidence-generation strategies, reimbursement submissions, publications, and scientific communications. Collaborates with statistics, epidemiology, RWE, medical, and external scientific teams to translate complex analyses into actionable conclusions.

The Principal Solutions Architect leads technical solution design, partners with hyperscalers, ensures architectural integrity, and drives customer engagement through compelling narratives and demos.

Manage strategic Central Government client relationships, identify and shape new business opportunities, lead bids, coordinate multidisciplinary teams, and develop value propositions. The role requires market intelligence, stakeholder engagement, and collaboration with technology, delivery, resourcing, and talent teams. Regular customer meetings across the UK and Bristol office attendance are expected. Candidates must be British passport holders who have lived permanently in the UK for five years and can obtain security clearance.

Build and own pricing data science capabilities, including demand and elasticity models, forecasting, willingness-to-pay models, pricing optimization, experimentation, and causal analysis. Deploy and monitor machine learning systems, establish governed pricing metrics, and partner with Commercial, Finance, and Product to improve margin and revenue. Set analytical standards for pricing decisions and build reusable analytical capabilities.

Own and improve production machine learning pipelines focused on accuracy, efficiency, and trustworthiness. Build LLM evaluations, judges, datasets, metrics, and benchmarks; run experiments across prompts, models, and pipeline designs; and reduce LLM costs through smaller task-specific models. Expand anonymization capabilities, evaluate open-source models, and collaborate with quality engineers to ship reliable ML features. Document findings and communicate technical trade-offs clearly.

Leads product strategy execution for a domain, manages and develops Product Managers, drives portfolio prioritization and OKRs, and ensures measurable outcomes. Coaches teams on discovery, AI-first workflows, customer engagement, stakeholder alignment, and regulated GxP software development. Partners with strategy, engineering, sales, and customer-facing teams while maintaining product quality, regulatory readiness, and cohesive cross-domain execution.