Top Machine Learning Jobs in Bristol

Manage and expand strategic partner alliances for SailPoint’s enterprise software business. Develop joint business, marketing, technical certification, and go-to-market plans; generate partner-sourced pipeline; coordinate account mapping, co-selling, enablement, promotions, and implementation capacity. Serve as the primary liaison between SailPoint and partner organizations, monitor performance and KPIs, ensure compliance and delivery quality, and present quarterly business assessments. The role requires extensive enterprise partner-management experience, analytical skills, executive communication, and approximately 50% travel.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Conduct research on AI compute, machine learning algorithms, large language models, efficient inference, numerics, world models, molecule generation, or model safety. Implement models and algorithms in Python or C++, design and analyze experiments using frameworks such as PyTorch, and communicate findings through technical presentations or research papers under experienced mentorship.

Graduate Machine Learning Engineers will implement, train, optimize, and benchmark AI models on Graphcore accelerator hardware. Responsibilities include profiling performance, designing and explaining experiments, identifying bottlenecks, contributing fixes across models and software, and collaborating with research, software, and product teams. The two-year programme provides hands-on experience spanning low-level kernel optimization, research algorithms, accelerator systems, and large-scale AI applications.

Manage a team of machine learning engineers developing credit and lending models for international markets. Set technical strategy, guide advanced ML solutions, partner with product, engineering, analytics, design, and risk teams, and ensure scalable underwriting capabilities. Provide hands-on technical leadership, clarify complex problems, manage trade-offs, and mentor engineers while contributing to Affirm’s long-term machine learning strategy.

Own the strategy, roadmap, development lifecycle, and go-to-market activities for fraud analytics products. Lead customer discovery, prioritize product improvements, analyze complex data, collaborate with development and data science teams, and use market and customer insights to improve user outcomes. The role requires fraud prevention expertise, statistical modeling and AI/machine learning knowledge, strong stakeholder communication, and flexible UK-US working hours.

Lead hands-on machine learning engineering across applied R&D, large-model training, LLMs, agentic systems, data pipelines, and edge deployment. Own technically demanding projects, make architecture decisions, train and optimize models, and mature systems for production or deployment. Represent the company with customers and partners, contribute to bids, mentor engineers, and establish engineering standards. The role focuses on trusted AI systems for demanding environments and requires regular on-site work in Bristol, occasional customer travel, and international exercises.

Conduct security research within HP’s Security Lab, exploring endpoint, infrastructure, supply chain, cryptographic, trusted hardware, firmware, privacy, and edge AI security technologies. Responsibilities include reviewing state-of-the-art research, identifying novel technical approaches, designing solutions, and demonstrating feasibility through prototypes or papers while collaborating with cross-disciplinary research teams.

Provide privacy compliance guidance to Research, Design and Development and Connectivity teams. Integrate Privacy by Design into product development, conduct privacy impact assessments, develop privacy frameworks and training, monitor evolving privacy laws, and support global privacy initiatives. The role advises stakeholders on responsible personal data use and emerging technologies, including artificial intelligence, machine learning, and IoT.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Develop and deliver machine learning and analytics solutions using predictive modeling, computer vision, and generative AI. Improve Verisk products and processes while ensuring accuracy, interpretability, and timely delivery. Stay current with analytic innovations, mentor analytic interns, and share methodologies across the analytics community. Work with large, complex datasets across insurance, energy, financial services, and other industries.

Lead strategic relationships with Capital Markets organizations across EMEA, driving adoption of NVIDIA AI and accelerated computing solutions. Serve as the primary client contact, grow revenue and platform usage, develop account strategies, forecast business, and engage senior technology leaders. Collaborate with solution architects, business development, developer relations, cloud partners, hardware providers, and software developers. Communicate solution value, provide thought leadership, and travel to meet clients and partners.

Software engineering intern supporting the Platform Engines group and Policy Engine for SailPoint’s cloud identity security platform. Responsibilities include developing software, procedures, and test solutions; collaborating with software and QA engineers, technical writers, and product managers; and working in Agile teams. The intern will gain exposure to cloud and software technologies including Golang, Angular, AWS, Docker, Kafka, Kubernetes, REST, SQL, and Temporal.

Build and support secure full-stack web applications, internal tools, APIs, data pipelines, and database schemas. Develop AI agents and LLM-powered solutions using Agentic AI, RAG, tool calling, guardrails, and Microsoft Foundry. Deploy machine learning models for predictive analytics, implement automated testing and CI/CD, resolve application and data issues, and modernize legacy systems. Collaborate with technical teams and business stakeholders to deliver scalable information and decision-support solutions.

Lead technical discovery, solution design, demonstrations, and proof-of-concept support for Anaconda’s AI and data science platform across EMEA. Partner with sales on complex opportunities, translate technical capabilities into business value, create reusable technical content, represent customer feedback to product teams, and coordinate cross-functional handoffs through implementation. Manage multiple concurrent sales cycles while supporting pipeline growth, deal expansion, and faster closes.

Lead and grow Rowden’s software engineering function, setting standards for architecture, development, testing, CI/CD, secure development, and assurance. Provide technical leadership on complex systems spanning software, hardware, AI, embedded platforms, and constrained networks. Build team capability, recruit and mentor engineers, manage resourcing and delivery risk, and establish a scalable SDLC and software assurance roadmap for mission-critical products.

Lead technical pre-sales engagements for enterprise email security customers. Partner with sales teams, conduct workshops and presentations, architect tailored solutions, and guide migrations from legacy Secure Email Gateways to Abnormal AI’s API-based platform. Build trusted customer relationships, troubleshoot migration challenges, provide product feedback, develop enablement content, and represent the company at industry events.

Build and maintain production-quality test infrastructure for Graphcore’s machine learning software stack and AI accelerator hardware. Design scalable test frameworks, CI/CD pipelines, and representative ML workloads across simulators, emulators, and physical hardware. Analyze numerical accuracy and performance results, improve testing and developer tooling, contribute to software architecture, collaborate across teams, and mentor junior engineers.

Design and build production-quality ML software test infrastructure, scalable test frameworks, and CI/CD pipelines spanning simulators, emulators, and physical AI accelerator hardware. Develop representative machine learning workloads, analyze execution results, improve testing and developer tooling, and contribute to software architecture and engineering practices. The role also involves mentoring junior engineers, conducting design and code reviews, and working with Python, C/C++, Linux, and automated testing systems.

Develops software tests for machine learning workloads on Graphcore accelerator hardware. Responsibilities include creating representative workloads, analyzing numerical accuracy and performance, designing tests, improving test infrastructure, building CI/CD pipelines, debugging issues, and collaborating with development teams to improve software quality. The two-year graduate program provides practical experience across machine learning, automation, performance analysis, and simulated and physical hardware platforms.

Provides customer-facing threat analysis and fraud prevention expertise for behavioral biometrics solutions. Responsibilities include advising financial institutions, analyzing fraud detection performance, deploying rules for attacks, supporting data science research into emerging threats, delivering reporting and insights, educating customers, leading workshops, and contributing to sales enablement and product strategy.

Leads complex customer audits, due diligence, and RFI/RFP engagements; oversees compliance response quality, customer communications, governance, process improvement, tooling, and team development. Partners with Sales, Legal, Information Security, and executives to address high-risk inquiries, maintain response documentation, improve workflows, and ensure accurate, customer-ready outputs.

Develop data-driven insights, predictive models, optimization solutions, and simulation-based decision-support tools for semiconductor manufacturing. Analyze manufacturing and operational datasets, apply statistical and machine-learning techniques, design experiments, and improve planning, scheduling, resource utilization, and factory performance. Collaborate with customers, domain experts, and engineering teams, communicate findings to technical and non-technical audiences, and contribute to manufacturing intelligence research and innovation.

Drive enterprise software sales through prospecting, product demonstrations, technical value communication, negotiation, closing, and customer expansion. Serve as the primary customer contact, maintain CRM and forecasting data, collaborate with product and engineering teams, gather customer feedback, and support adoption. The role focuses on Replit’s AI-powered developer platform and requires London-area availability with travel up to 25%.

Principal Engineer responsible for building and operating production software at scale across multiple codebases. The role involves shipping end-user products, improving event and data pipelines, diagnosing performance bottlenecks, influencing technical direction, establishing agentic engineering practices, and collaborating with data scientists. This hands-on individual contributor role requires broad experience across Python, Node.js, React, Rust, data science, cloud infrastructure, security, privacy, and regulated financial software.