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.

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.

Supports enterprise sales by discovering customer requirements, mapping them to SailPoint solutions, and delivering foundational implementations and proof-of-value engagements. Acts as a technical lead and consultative advisor, educating customers on architecture and best practices. Collaborates with sales, product, professional services, partners, and customer success teams while developing AI-driven and agentic solutions for demonstrations and customer outcomes.

Lead and mentor a data science team developing machine learning systems for threat detection and agentic AI. Set ML technical strategy, standards, roadmaps, and deployment practices; guide projects from research through production; collaborate with security, engineering, and product teams; develop advanced malware and behavioral threat models; communicate insights; and contribute to research, publications, patents, and hands-on technical work.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

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.

Provide expert technical advice on age assurance and digital identity technologies within online safety regulation. Lead research and evaluations, assess technical feasibility and risks, translate complex concepts for policy and leadership audiences, prepare briefings and demonstrations, monitor emerging trends, and engage with academia, industry, public bodies, and external technical groups.

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 biomedical data science for clinical and health research, integrating clinical, observational, EHR, genetic, wearable, electrophysiological, and video data. Develops signal-processing methods, machine-learning models, probabilistic and time-series analyses, scalable data pipelines, and reproducible workflows. Validates clinically relevant models, supports disease phenotyping and predictive modeling, ensures compliance with pharmaceutical and healthcare standards, and communicates technical findings to clients and stakeholders.

Conduct computational analyses of genomic, transcriptomic, proteomic, and other biomedical datasets to identify drug targets, biomarkers, and disease subtypes. Apply machine learning, deep learning, and omics methods; integrate multi-omics data; review literature; interpret results; design validation strategies; and develop visualizations and reports. Collaborate with AI, biology, chemistry, imaging, and medical experts while contributing to agentic AI systems and internal research methodologies.

Lead regional field sales teams, develop sales strategies and account plans, manage pipeline and forecasts, recruit and coach sales managers, close enterprise technology deals, and grow business through customers, resellers, and partners. The role requires strong technical knowledge of cybersecurity, cloud, networking, and IT infrastructure solutions, executive-level selling skills, and the ability to manage remote teams across the NEMEA region.

Leads the mid-market business development function, including team building, territory strategy, prospecting, negotiation, closing, pipeline management, and account acquisition and retention across pharma and biotech. Partners with marketing, strategy, and commercial operations on go-to-market execution. Represents the company at industry events and develops relationships with clinical trial sponsors while selling complex AI-powered SaaS solutions.

Own the vision, roadmap, and delivery of AI-powered functionality across the IRIS Elements Platform. The role involves researching customer needs, prioritizing product opportunities, launching scalable AI features, establishing evaluation frameworks, and collaborating with Engineering, Design, Data, and Commercial teams. The successful candidate will shape AI strategy, promote responsible AI practices, monitor market developments, and deliver measurable value for accountancy software customers.

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.

Conduct world-leading interdisciplinary research within the Decisions Cluster of the Leverhulme Centre for Algorithmic Life, examining how AI and algorithmic technologies transform decision-making. Develop research and funding plans, collaborate across disciplines, contribute to knowledge exchange and the research environment, support postgraduate research students, and undertake academic administration and citizenship activities.

Leads a 25+ person organization of data scientists, machine learning engineers, and analytics engineers across Identity and Financial Crime. Owns data quality, governance, lineage, observability, fraud and financial-crime models, production performance, monitoring, retraining, and domain data products. Partners with engineering, product, risk, compliance, legal, and central data teams; influences upstream teams, develops managers and senior ICs, handles incidents, and scales hiring and technical strategy.

Own and build Oversee’s product marketing function, including ICP definition, positioning, persona messaging, competitive and win/loss research, product content, sales enablement, and end-to-end product launches. Partner closely with product, sales, growth marketing, and executives to translate technical AI and travel technology capabilities into compelling commercial messaging, establish repeatable GTM processes, and measure launch performance.

Develop statistical and machine learning models using soccer tracking and event data to support player recruitment decisions. Build spatio-temporal models, metrics, analyses, and interpretation tools; validate models; communicate findings to professional club clients; and partner with engineering on cloud deployment and production reliability. The role also includes code review, model maintenance, and advancing analytical methods.

Build and improve Firefox WebCompat internal dashboards, reporting tools, and broken-site screenshot capture pipelines. The role involves creating reliable data views for triage and metrics, automating screenshot workflows, collaborating with WebCompat and QA teams, and translating reporting needs into effective tooling. Familiarity with WebCompat workflows, Bugzilla, screenshot automation, and machine learning is preferred.

Leads Tide’s global engineering organization for ongoing monitoring, fraud detection, financial crime, sanctions, and regulatory-risk platforms. Owns engineering strategy, shared decisioning capabilities, ML model lifecycle, agentic AI governance, platform scalability, and measurable risk and efficiency outcomes. The role manages distributed engineering, data science, and analytics teams while aligning risk, compliance, operations, payments, product, and technology stakeholders across multiple markets.

Lead and scale 24/7 security operations for MDR clients, managing SOC leaders, analysts, monitoring, threat detection, investigations, and incident response. Drive SOC process improvement, automation, AI-enabled capabilities, operational KPIs, SLAs, and service quality. Partner with security and customer-facing teams, serve as the senior escalation point for major incidents, and strengthen geographically distributed security operations.

Build and operate scalable cloud data pipelines, warehouses, transformation layers, and ML production systems. Lead data infrastructure architecture, warehouse performance optimization, DataOps monitoring, CI/CD improvements, data quality testing, and large-scale data product delivery. Collaborate across teams, promote data stewardship, and support batch and streaming pipelines while deploying, serving, and monitoring machine learning models.

Lead digital delivery and optimization across AECOM’s England and Wales water operations. Develop digital strategies, advise clients on transformation, data governance, operating models, and platform adoption, and identify AI, automation, and data science opportunities. Lead digital workplans, client workshops, stakeholder engagement, bid responses, and regional team adoption of digital solutions. Partner with account managers and delivery teams to build opportunities and deliver measurable outcomes across complex infrastructure programs.

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.