546 jobs for “ai analyst”
CrowdStrike Ireland
Builds and operates large-scale distributed data pipelines, storage and presentation layers for the Intelligence team, owning systems from design and prototyping through production operations. Works autonomously with internal analyst customers, choosing the tech stack and maintaining both new and legacy Go and Python services.
CrowdStrike Romania
Builds and operates large-scale data processing pipelines, storage systems and presentation layers for the Intelligence team, owning systems from design through prototyping, implementation and production operations. Works autonomously on a distributed remote team, gathering requirements from analysts and choosing the technology stack, with existing Go and Python codebases to maintain.
Harnham - Data and Analytics Recruitment London £100,000 – £120,000 pa
Sits within a private equity firm's value creation function, designing and building scalable data platforms and architecture for portfolio companies. Works hands-on with SQL and Python to establish data engineering foundations for analytics and AI-ready environments, while advising C-suite stakeholders across varied data maturity levels and technology stacks.
Darktrace Cambridge
Owns the Network Detection and Response product roadmap end to end, deciding what gets built and in what order. Works directly with customers running zero-trust, cloud-connected and segmented estates, partners with R&D on prioritisation and testing, and supports Product Marketing on launches and go-to-market. Acts as internal subject matter expert for the NDR portfolio.
Darktrace London
Owns the end-to-end roadmap for Darktrace's Network Detection and Response product, deciding what gets built and in what order. Works directly with customers running complex zero-trust, cloud-connected and segmented estates, partners with R&D on prioritisation and testing, and supports Product Marketing on launches and go-to-market. Acts as the internal subject matter expert for the NDR portfolio.
Isomorphic Labs Cambridge, United States
Lead computational drug design programs from initiation through to clinical candidate selection, applying AI-first approaches and shaping the company's ML drug design engine. Work cross-functionally with ML, biology and chemistry teams, with optional people management of 2-3 computational chemists.
Amazon London
You will act as a trusted technical advisor to AWS customers in the Betting & Gaming industry, leading architecture reviews, white-boarding sessions, demos and workshops while managing the overall technical relationship. The role blends business acumen with hands-on guidance across AI, serverless, containers, analytics and DevOps, and involves feeding customer needs back into AWS product roadmaps.
ElevenLabs United Kingdom
Build and operate production-grade abuse detection and guardrail systems, focusing on free-tier abuse, fraud, and bot farming across a multimodal platform. Own the safety infrastructure end to end, from architecture and APIs to data pipelines, monitoring, and SLIs/SLOs, working with ML and full-stack engineers to move research models into production.
PhysicsX London
Builds the simulation side of Large Physics Models, generating multi-fidelity CFD data to train large-scale ML models. Develops solvers and numerical methods in differentiable or GPU-native frameworks such as JAX or NVIDIA Warp, using commercial and open-source CFD tools for reference data. Works in a research team alongside ML researchers, shaping data generation strategy and fidelity tradeoffs.
PhysicsX New York, United States US$150,000 – US$190,000 pa
Delivery-focused role embedding physics-aware AI models into customer tools, working on-site with clients across aerospace, automotive and energy. Involves building reliable ML data pipelines, manipulating 3D point-cloud and mesh data, and translating R&D outputs into reusable libraries and products. Expects travel of 3-4 weeks per quarter to customer sites worldwide.
Reperio Human Capital Dublin, Ireland £388 – £474 pd
Hands-on engineering role owning AI/ML initiatives end-to-end, from solution design and experimentation through deployment, monitoring and optimisation. Involves building production ML and GenAI solutions including RAG architectures, working with Snowflake and cloud data platforms, and developing Python and R software with strong MLOps, CI/CD and DevSecOps practices. Collaborates with data, product and business teams to turn ambiguous problems into scalable, secure solutions.
Luminance Cambridge
Owns the software development lifecycle that produces packaged releases of an enterprise legal AI platform for distribution to clients. Day to day involves keeping the lifecycle efficient, unblocking the tech team, and analysing the SDLC for weak points to build human or automation solutions improving efficiency, reliability and visibility.
Databricks London
Drives large-scale enterprise data warehouse migrations onto the Databricks Intelligence Platform across EMEA, partnering with GTM leadership, product specialists and account teams to shape adoption strategy. Acts as the tier-3 escalation point for complex or stalled migrations, builds assessment tooling and programmatic migration assets, and mentors the regional Solutions Architect community. Also feeds field insights back to Product and Engineering and authors whitepapers and conference talks.
OpenAI London
Lead and grow a London-based engineering team building real-time safety and oversight systems for AI agents, including the Auto-review permission-boundary model. The role blends hands-on technical work—shaping architecture, reviewing designs, debugging, and coding—with hiring, coaching, and setting the operating cadence. It is highly cross-functional, partnering with alignment researchers, product, security, and infrastructure teams.
Wayve London
Lead the Applied Methods Data Science team, partnering with the Autonomy organisation to turn experimental and observational analysis of real and simulated driving into evaluations and insights. Set three-, six- and 12-month roadmaps, review technical proposals for statistical rigour, hire and grow data scientists, and build tooling to scale the team's capability.
