Top Machine Learning Jobs in Bristol

Lead and grow a distributed engineering organization building customer-facing security capabilities: proprietary scanners, AI/ML detection engines, agentic remediation, vulnerability management, and security foundations. Set vision and roadmap, drive architecture and delivery, partner with product management, establish engineering standards, and represent the group in cross-functional and customer forums.

CrowdStrike seeks a Senior Intelligence Analyst to provide threat intelligence and digital risk monitoring, collaborating with teams to deliver customer-focused solutions and presentations, while maintaining customer relationships.

As a Product Manager at Bringg, you will define product strategy, work with stakeholders, manage the roadmap, and integrate AI into logistics solutions.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead and manage an ML engineering team building post-origination credit models for repayment, collections, recovery, and loss mitigation. Define technical strategy, design and scale ML solutions, partner with product, engineering and risk, mentor engineers, and operationalize models to minimize loan loss and personalize collections.

As ML QA Technical Product Owner, coordinate backlog management, support sprint planning, and facilitate cross-team communication to validate machine learning software effectively.

Senior individual-contributor responsible for net and gross revenue retention across enterprise accounts, driving renewals and expansions with compliance/AML stakeholders, and acquiring one strategic channel partner end-to-end (market mapping, negotiation, onboarding). Acts as customer voice to product and leads cross-functional account strategy, risk mitigation, executive reviews, and partner enablement.

The Staff Scientist leads significant research areas, designs research projects, engages with real-world applications, mentors other scientists, and represents the organization's scientific authority externally.

Validate and benchmark ML models across Graphcore's software and hardware stack. Build automated benchmarking pipelines, run open-source models, create targeted tests for numerical precision, quantisation, attention, distributed execution and model subgraphs, and debug performance and correctness issues.

Validate and benchmark ML models and the Graphcore software/hardware stack. Design and run automated benchmarks, targeted tests for numerical precision, quantisation, attention and distributed execution, expose regressions and performance limits, run open-source models, debug system and model behaviour, and collaborate with software, infrastructure and hardware teams.

Design and build scalable test infrastructure, automation, and tooling to validate ML software stacks and hardware. Shape test architecture across large codebases, CI pipelines, and representative ML workloads. Mentor engineers and improve testing practices to increase reliability and performance.

Designs and deploys supervised machine learning classifiers using curated patent data, conducts desk research on technologies, scopes and defines client classifier taxonomies, supports customer meetings and data review, and delivers ad-hoc analysis and presentations as projects progress.

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.

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.

Join a hybrid Bristol-based engineering team designing, integrating, and delivering robust systems for degraded or denied operational environments. Responsibilities include translating user needs and CONOPS into requirements, applying systems engineering lifecycles, leading integration and architecture tasks, assessing trade-offs and risks, ensuring safety/security compliance, and mentoring junior engineers. SC clearance eligibility required.

Lead platform product ownership bridging cloud and firmware strategy and execution. Manage and prioritize backlog, engage customers, collaborate with R&D, define releases, and drive agile delivery aligned with product leadership.

Own the Device Intelligence product roadmap for tier‑1 network service providers. Define PRDs, AI/LLM-assisted workflows, and technical requirements; lead discovery, backlog prioritization, and cross-functional delivery; engage strategic customers and support sales with competitive positioning.

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

As a C++ Engineer, you will develop machine learning features, integrate models, maintain SDKs, and collaborate across teams for software performance and enhancements.

The Data Scientist will analyze conversational data to provide insights, enhance AI capabilities, and deliver value for Fortune 500 clients.

As a Machine Learning Engineer, you will design and enhance models for conversational AI, addressing challenges in NLP and enterprise deployment.

As Senior Product Manager, you'll lead the integration of global airline partners, optimize supply metrics, and enhance product specifications for seamless booking automation, focusing on AI solutions and API performance.

The Staff Software Engineer (ML QA) will design, maintain test automation for ML software, and mentor junior engineers while fostering a culture of software quality.

Lead and deliver statistical support for Phase II-III clinical trials embedded with a sponsor: design input, SAP/sample size, interim/final analyses, oversight of programmers/statisticians, regulatory submissions, and collaborate cross-functionally to ensure compliant, high-quality statistical deliverables. Apply advanced statistical methods and ML/DL for analytics and process automation.

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.