Artificial Intelligence Jobs

Wayve · London

Hands-on role optimising inference for edge accelerators and GPUs so large transformer models run efficiently on low-cost, low-power in-vehicle compute. You'll profile model graphs, compiler/runtime behaviour and kernel execution, implement optimisations like fusion, scheduling and custom kernels, and build benchmarking and regression tests across NVIDIA Orin/Thor and Qualcomm targets, working closely with model, platform and deployment teams.

Wayve · London

Set the technical direction for a petabyte-scale storage platform underpinning autonomous driving data, leading a multi-quarter programme from architecture to adoption. Build production services and controllers in Python or Go with Kubernetes and Terraform, optimising read performance, caching and cost while partnering with ML, data, security and privacy teams.

University of Cambridge · Cambridge · £63,606 – £67,468 pa

The role involves contributing to research and teaching in artificial intelligence and machine learning, with a focus on fundamental ML, novel models and architectures. The appointee will develop graduate content for the MPhil in Advanced Computer Science, contribute to undergraduate teaching, and build a research team supported by external funding.

Isomorphic Labs · London

Join the Computational Sciences team to design novel large-molecule therapeutics using a cutting-edge AI drug design engine. You'll develop machine learning methods to predict biologics properties from sequence, benchmark models, and analyse lab data to guide early discovery through candidate selection.

Isomorphic Labs · London

Lead all externalised drug discovery and preclinical lab operations, building and scaling a global CRO infrastructure for an AI-first drug design platform. Oversee experimental throughput, data QC and turnaround times, embed data-generation-by-design standards with Data Engineering, and manage vendor governance, budgets and a team of CRO Scientific Leads, Operations Managers and Compound Managers.

Databricks · London

Serve as the trusted technical ML and AI expert for enterprise customers, architecting production-grade ML and GenAI workloads on the Databricks platform. The role spans RAG architectures, agentic systems, MLOps lifecycle management, and cloud-native integration, while mentoring colleagues and influencing the product roadmap. It combines deep hands-on engineering with customer-facing technical sales support.

Barclays · London

Owns the optimisation and strategy of transaction monitoring controls across Barclays UK and International, tuning surveillance systems and developing detection solutions. Involves data exploration, SQL/Scala/Spark/Python coding, and engaging technical and non-technical stakeholders on financial crime risk. Based in Canary Wharf or Glasgow.

NVIDIA · Reading

Serve as the first line of technical expertise between NVIDIA, Hyperscaler partners and end-customers, with a primary focus on the Google Cloud (GCP) partnership. Develop and demonstrate GenAI and accelerated computing solutions, optimise GPU training and inference pipelines, and engage developers, researchers and senior technical leaders.

Amazon · London

Lead end-to-end delivery of complex AI/ML engagements for enterprise customers, from strategic planning through pre-production deployment and optimisation. Architect solutions on AWS services with a focus on Generative AI using Amazon Bedrock and SageMaker, while mentoring junior consultants and supporting pre-sales scoping. Based in AWS UK offices when not at customer sites.

Harnham - Data and Analytics Recruitment · London · £120,000 – £150,000 pa

Lead and build a data science function within a fintech, owning strategy across risk, affordability and lending decisioning. Design, build and deploy machine learning models using credit risk, Open Banking and customer data, working with Product, Engineering and Credit Risk teams. Requires hands-on Python, SQL and MLOps experience plus credit risk modelling in UK consumer lending.

NVIDIA · France

Serve as the first line of technical expertise between NVIDIA, hyperscaler partners and end-customers, with a primary focus on the Google Cloud (GCP) partnership. Day to day involves proof-of-concept demonstrations, optimising GPU-accelerated training and inference pipelines, and engaging developers, researchers and technical executives to evangelise accelerated computing and Generative AI.

Vallum Associates · London · £475 – £500 pd

Data scientist role focused on collecting and analysing large datasets, building experimental models and machine learning applications in Python, and performing complex statistical analysis. Involves leading small teams on data science products, developing classical ML and LLM solutions with prompt and RAG techniques, and mentoring junior data scientists. Hybrid working with two days per week in the London office.

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.

Bowers Partnership · London · £825 pd

Hands-on VP-level data scientist building generative AI, LLM/NLP and statistical modelling products end to end, from prototype to production, for a boutique investment bank's M&A and advisory bankers. Works in a small team, writing production-quality Python and explaining models and assumptions directly to senior non-technical stakeholders. M&A experience is essential; hybrid with at least three days a week in the London W1 office.

Relation Therapeutics · London

Develops and benchmarks machine learning models for DNA sequence, regulatory elements and genetic variation, including variant effect prediction and representation learning. Integrates sequence-derived representations with transcriptomic, epigenomic and perturbational data to uncover disease mechanisms and support target prioritisation, working within the interdisciplinary Rosalind team.