Top Machine Learning Jobs in Bristol

Perform malware and threat research across the attack lifecycle, validate and improve Falcon detections, collaborate with engineering and ML teams, automate analysis, support external security testing, and translate findings into product protections.

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.

Lead and mentor a data science team building ML and LLM solutions for cybersecurity. Translate business needs into research and production ML objectives, prioritize roadmaps, collaborate cross-functionally, and drive technical vision, model development, and operationalization for malware detection and threat analysis.

Build AI and automation solutions using Microsoft Fabric, Power Platform, LLMs, intelligent document processing, agentic AI, and Power BI. Lead responsible AI practices, stakeholder discovery, training, adoption, and MVP delivery across capital project consulting. Maintain billable involvement in Technical Due Diligence engagements, identify client-facing AI opportunities, and support proposals and commercial delivery. The role requires Python, SQL, data pipeline development, governance awareness, strong communication, and UK work authorization.

Designs, builds, integrates, tests, and deploys scalable AI and cloud solutions for clients. Leads discovery, architecture, feasibility assessments, proof-of-concepts, bids, and initial delivery increments. Develops APIs, integrations, and data pipelines; evaluates ML and LLM technologies; and advises stakeholders on responsible AI adoption. The role requires strong software engineering, architecture, client engagement, communication, and technical ownership skills across pre-sales and implementation.

Participate in Airbus’s two-year graduate development programme within the Structures Test team. Rotate across test leadership, mechanical test means engineering, advanced test technologies, and test operations. Support structural testing of materials, components, and aircraft structures; develop measurement, control, data acquisition, simulation, and analytics methods; and contribute to sustainable aviation projects including lightweight materials and hydrogen-powered propulsion testing.

Two-year Airbus Global Graduate role developing software capabilities that support aircraft flight physics and overall aircraft design. Rotational placements will involve software development, automation, machine learning, data analysis, cloud computing, numerical modelling, and collaboration with aerodynamics, loads, aeroelastics, and mass-properties teams. The programme includes technical and soft-skill training, mentoring, project work, and leadership development.

Develop into an Airframe Automation Engineer through a two-year graduate programme. Responsibilities include analyzing and improving engineering business processes, delivering automation solutions from concept to deployment, optimizing workflows with digital tools, and exploring LLM, machine learning, deep learning, and knowledge graph technologies. The role includes rotational placements across airframe engineering and digital domains, providing experience in digital transformation, operational excellence, engineering delivery, and technical governance.

Leads the architecture and delivery of complex Azure, Microsoft 365, cloud, and AI solutions for strategic customers. Translates business needs into secure, scalable architectures; manages requirements, design governance, technical quality, deployment, and stakeholder alignment. Acts as a trusted technical advisor, drives presales and delivery outcomes, develops reusable intellectual property, mentors architects, and promotes Microsoft technologies through thought leadership and customer engagement.

Lead a small team of engineers while remaining hands-on in Java backend development. Design scalable services and integrations supporting campaign analytics, attribution, automation, AI-powered recommendations, and intelligent decisioning. Guide architecture, reliability, observability, and technical planning; coach engineers; and collaborate with Product, UX, ML, and data science teams to deliver trustworthy AI experiences and evaluation mechanisms.

Lead technically complex product work on Rosso, embedding with ML, data science and engineering teams to turn business and customer needs into shipped features. Define success criteria for models/forecasts, manage edge cases and operational risk, and prioritize work across portfolio, forecasting, pricing optimisation and related systems.

Leads the design and scaling of Databricks-based data, analytics, and AI platforms supporting global customer operations. Builds enterprise data pipelines, machine learning, NLP, generative AI, conversational AI, dashboards, and operational intelligence solutions. Establishes governance, data quality, CI/CD, reliability, and AI lifecycle standards while partnering with product, operations, engineering, workforce management, and AI teams. Provides technical leadership, coaching, and mentorship to engineers and data scientists.

Lead Mitek’s EMEA revenue strategy and execution across direct enterprise and channel sales for identity and fraud prevention platforms. Own regional growth, forecasting, pipeline, account expansion, partner ecosystem development, customer adoption, and revenue targets. Manage enterprise sales and account teams, negotiate complex multi-year agreements, support regulated-market customers, and report performance to the CRO while collaborating with Product, Engineering, Finance, Legal, Compliance, Customer Success, and global channel teams.

Serve as the technical SME for compliance automation, overseeing GRC control mapping, evidence collection, integrations, and continuous monitoring. Partner with engineering teams to embed compliance into workflows, support audits and framework rollouts, assign control ownership, reduce audit burden, and maintain audit readiness. Lead cross-functional initiatives and communicate compliance risks, control status, and progress to technical and leadership audiences. The role requires cybersecurity framework expertise, program management, cloud and API fluency, GRC platform experience, and familiarity with AI-enabled compliance workflows.

Reviews and evaluates engineering, infrastructure, and platform documents and work products for technical accuracy, completeness, clarity, consistency, and relevance. Provides structured feedback, identifies errors and gaps, compares technical approaches, and follows defined evaluation frameworks. Requires independent work, strong communication, analytical ability, and professional engineering judgment. The role is fully remote and supports varied technical evaluation projects as an independent contractor.

Lead technical strategy and architecture for personalization, search, and recommendation systems. Deliver scalable ML-powered features, mentor senior engineers, and improve engineering quality across cross-functional teams.

As a Principal Engineer at M&S, you'll drive technical strategy, influence architecture, and mentor engineers while delivering on personalization, search, and machine learning features in collaboration with cross-functional teams.

Own an AI stockbroking product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, security, scalability, and failure handling. Integrate KYC, transaction monitoring, privacy, licensing, and regulatory requirements. Apply AI with evaluation, safeguards, and human oversight while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Own an AI investing product vertical end-to-end, including strategy, roadmap, technical design, delivery, metrics, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Embed regulatory requirements across KYC, monitoring, limits, privacy, and licensing. Apply AI with evaluation, safeguards, human oversight, and reliability controls while aligning compliance, operations, finance, treasury, and design.

Owns an AI neobank product vertical end-to-end, including strategy, roadmap, technical design, delivery, regulatory requirements, AI evaluation, reliability, and launch. Partners with engineering, compliance, operations, treasury, finance, and design across payments, remittance, insurance, wealth, and trading products. Must balance correctness, scalability, security, user experience, cost, speed, and regulatory constraints in high-consequence financial systems.

Owns roadmap execution and capability definition for an Agentic AI Platform. Translates AI platform strategy into requirements, prioritized roadmaps, reusable agent orchestration and lifecycle capabilities, governance controls, observability, and scalable platform patterns. Partners with engineering, architecture, data, security, legal, compliance, customer success, professional services, and customers. Measures adoption, reliability, safety, quality, cost, and business impact while balancing technical feasibility, security, compliance, and customer value.

Develop advanced data science solutions for British Army training, safety, and operational challenges. Responsibilities include preparing and analysing data, applying statistical and machine learning methods, building predictive models and data products, creating reports and dashboards, and communicating insights to technical and non-technical stakeholders. The role also involves collaborating with military and technical teams, mentoring colleagues, and maintaining data governance, ethics, and security standards.

Build and extend the platform layer: design shared backend services and APIs, improve reliability and correctness, collaborate with product teams to remove platform bottlenecks, mentor engineers, shape architecture and migrations, and write high-quality fullstack code with a backend focus.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

Own the end-to-end product direction and quality of AI-powered email capabilities. Define requirements, evaluation frameworks, quality standards, and measurable outcomes while balancing model quality, latency, cost, reliability, safety, and user experience. Partner closely with ML, backend, and client engineers on system design, experimentation, failure handling, and iteration. Drive prioritization, technical decisions, execution, and user trust in a fast-moving zero-to-one environment.