605 jobs for “ai analyst”
CrowdStrike Germany
Builds and operates large-scale data processing pipelines, storage systems and presentation layers for the Intelligence team, owning systems from design and prototyping through production deployment and long-term maintenance. Works fully remotely with analysts as internal customers, choosing your own tech stack across Go, Python, SQL/NoSQL and cloud.
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.
Databricks United Kingdom
Customer-facing technical authority on Generative AI, LLMs and applied ML for digital-native and startup accounts across EMEA. Shapes architectures, builds hands-on proofs of concept and reference implementations on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog), and leads fine-tuning and evaluation engagements on open models. Also mentors the field engineering organisation and represents the company externally through talks and blogs.
University of Oxford Oxford £21,805 pa
Investigates how the rapid growth of AI can be supported by more sustainable, circular hardware and infrastructure, linking computational performance to the physical materials and equipment required. Develops scenarios for UK AI and data centre growth, mapping hardware requirements to critical raw materials and modelling how lifetime extension, reuse, repair and remanufacture could cut environmental impacts. Based in the Circular Economy and Sustainability Lab, contributing to the Circular Electricals and Electronics Project.
Databricks London
Lead and scale the UK Forward Deployed AI Engineering team, delivering professional services engagements that help EMEA customers productionise GenAI and ML applications. The role combines people leadership, executive customer relationships, and cross-functional work with Product, Research and Sales to shape delivery models and the product roadmap.
Wayve London
Owns validation strategy for ADAS and L2 autonomy functions, translating product, safety and regulatory requirements into test scenarios, metrics, coverage and acceptance criteria. Works hands-on with Python evaluation pipelines, simulation and SQL-based data analysis, spanning simulated and physical test environments. Open at senior IC or manager level, with close collaboration across Product, Safety and Release stakeholders.
University of East Anglia Norwich £21,805 pa
A PhD studentship developing multispectral and hyperspectral imaging combined with machine learning to detect and classify marine litter from aerial and drone-based platforms. The researcher will characterise litter material reflectance in the lab, curate imaging datasets, and build models robust to changing illumination and sensor differences, based in the Colour & Imaging Laboratory and working with CEFAS scientists.
University of Surrey Guildford £21,805 pa
Develops next-generation federated machine unlearning algorithms that deliver verifiable, robust erasure without harming model performance or participant privacy. Research spans certified unlearning with formal guarantees, robustness to adversarial relearning, federated-specific benchmarks, and scalable unlearning for foundation models, supervised by Dr Pedro Porto Buarque de Gusmao and Dr Frank Guerin.
Harnham - Data and Analytics Recruitment London £70,000 – £80,000 pa
Build, scale and maintain backend services including APIs, workflow engines and data services, integrating Java/Spring components with Python-based AI services. Work across AWS cloud infrastructure, CI/CD pipelines, observability and security best practices in a collaborative, fast-paced product team.
Harnham - Data and Analytics Recruitment London £75,000 – £85,000 pa
Owns the infrastructure, deployment and operational excellence of production machine learning systems within a growing AI and data organisation serving the public sector. Builds ML orchestration pipelines with Dagster, Airflow or Prefect, runs Kubernetes and Terraform/Bicep infrastructure, and maintains CI/CD and observability for models and LLM-powered solutions, working closely with data scientists and client-facing teams.
Scale AI United Kingdom
Finance experts design and evaluate complex financial scenarios—valuation, forecasting, risk assessment and equity research—to test and improve generative AI models, giving detailed feedback on outputs for market relevance and compliance. Fellows may co-author research publications with Scale's team and work flexible 10–40 hour weeks within an interdisciplinary network.
Scale AI London
Leads a forward-deployed engineering team acting as the technical bridge between AI capabilities and strategic enterprise customers. Involves designing custom integrations, ETL pipelines and production AI agents, plus prompt engineering, RAG systems and evaluation frameworks, deployed within customer security and compliance boundaries.
Signal AI London
Full-stack engineer owning revenue-critical products end to end, from problem discovery with research, design and product through to production. Day to day involves building UIs and data visualisations, large-scale distributed services, AWS infrastructure and observability, with heavy pair programming and AI-assisted development using tools like Claude Code.
Isomorphic Labs Cambridge, United States
Lead the safety assessment strategy for drug discovery projects from inception to regulatory submission, designing screening cascades and mechanistic experiments for small molecules and biologics. Partner with machine learning researchers to build predictive toxicology models and manage CRO relationships for outsourced wet-lab data generation, while mentoring junior scientists.
Isomorphic Labs London
Research engineers translate frontier research concepts into practical implementations, building and optimising state-of-the-art AI models such as Transformers, GNNs and diffusion models, plus the codebases, data pipelines and infrastructure for training and evaluation. They design and run experiments, analyse model performance, and advise on bringing models to production, working closely with research scientists in a cross-disciplinary team.
