538 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 £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 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.
Isomorphic Labs Cambridge, United States
Lead and execute the translational medicine strategy across oncology programs, ensuring clinical biomarker assay readiness and data delivery to inform mechanism of action, resistance and future indications. Serve as a core program team member and cancer biology expert, collaborating with AI and computational biology teams to build innovative biomarker analysis tools and advance companion diagnostics.
Darktrace Cambridge
Works within Cambridge R&D teams on high-impact projects spanning rapid prototyping and structured platform development, providing expert technical direction and mentoring engineers across languages such as Python, JavaScript, Rust and C++. Involves advancing methodology for defending against unknown cyber-attacks, shaping technical strategy, and engaging with executive leadership. Hybrid role with two days a week in the Cambridge office.
Darktrace London
Works within the Cambridge R&D teams on high-impact projects spanning rapid prototyping and structured platform development, advancing methodology for defending against unknown cyber-attacks. Provides expert technical direction, mentors engineers across languages like Python, JavaScript, Rust and C++, and engages executive leadership on technical strategy. Requires Docker, cloud, CI/CD and Git proficiency with a strong interest in cyber-security and malware forensics.
Noir Abingdon US$170,000 – US$195,000 pa
Take full ownership of the technology function at an early-stage AI venture, making key architectural decisions and building a founding engineering team. The platform combines proprietary data, real-time insights and advanced AI (LLMs, RAG, AI agents) for a specialised luxury and wealth intelligence market. The role blends hands-on engineering with founder-level strategy and equity.
Noir London £160,000 – £180,000 pa
Take full ownership of the technology function at an early-stage AI venture, making key architectural decisions and building a founding engineering team. The platform combines proprietary data, real-time insights and advanced AI, with work spanning LLMs, RAG pipelines, AI agents, data infrastructure and cloud architecture. It is a hands-on founder role rather than a traditional management position.
NVIDIA Switzerland
Develops performance optimizations in deep learning frameworks using JAX, contributing to JAX core components and driving peak performance on NVIDIA hardware. Works with AI researchers to build future-proof models and tooling that bridges numerical computing, simulation and deep learning research. Requires C/C++ and Python skills plus deep knowledge of ML framework internals and CPU/GPU architectures.
NVIDIA United Kingdom
Develops performance optimizations in deep learning frameworks using JAX, contributing to JAX core components and driving peak performance on NVIDIA hardware. Works with AI researchers to build future-proof models and tooling that bridges numerical computing, simulation and deep learning research. Requires C/C++ and Python, ML framework internals, and CPU/GPU architecture expertise.
