Artificial Intelligence Jobs

• London
• Hybrid · 3 days in office
• Senior

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.

AlphaFold

• London
• Hybrid · 3 days in office
• Lead

Design and evolve a large-scale ML infrastructure platform that supports distributed training and inference workloads, working closely with research, engineering and product teams. The role also explores deploying agents to improve platform robustness and reliability, in a hybrid London setup requiring three office days a week.

Kubernetes · Google Cloud Platform · GCP

• United States
• Remote
• US$120,000 – US$185,000 pa
• Mid-level

Builds and operates core systems for the Falcon Complete team, developing features that help security analysts triage and remediate threats at scale. Work spans Golang, microservices, Kafka, Kubernetes and cloud-native tooling, with on-call rotations and heavy async collaboration across a US/UK distributed team.

AWS · Azure · GCP +7

• United States
• Remote
• US$140,000 – US$220,000 pa
• Senior

Builds and operates core systems for the Falcon Complete team, designing reliable, scalable services that help security analysts triage and remediate threats at scale. Work spans Golang, microservices, data pipelines, Kafka, Kubernetes and cloud observability, with on-call rotations and close collaboration with analysts across the US and UK.

AWS · Azure · GCP +6

• New York, United States
• Hybrid
• US$90,000 – US$130,000 pa
• Mid-level

Customer-facing role owning the full customer journey for physics AI solutions, from onboarding and change management to roadmap planning and contract preparation. Works alongside simulation, software, ML engineers and data scientists, running account rhythms, tracking adoption and building AI-enabled tooling for account operations.

• New York, United States
• Hybrid
• US$150,000 – US$250,000 pa
• Lead

Customer-facing role owning the full customer journey, from onboarding and change management to roadmap planning and contract preparation. Works alongside simulation, software, ML engineers and data scientists to translate engineering and physics challenges into product opportunities, tracking engagement and measuring value. Based in Manhattan with hybrid remote flexibility.

• London
• Hybrid
• Permanent

Builds Python services and microservices that orchestrate the end-to-end model-release workflow, integrating feature candidates into release branches and automating readiness checks before training. Connects training platforms, simulation and on-road testing, and productionises services on Azure and Kubernetes with observability and approval gates.

Azure · Kubernetes · React +1

• United Kingdom
• Remote
• Senior

You will own a small portfolio of strategic software companies, acting as their trusted technical advisor to integrate NVIDIA's AI platform, open models, SDKs and NIMs into their products. The role blends hands-on agentic AI and GPU-computing depth with developer advocacy, ecosystem mapping and commercial storytelling to engineering and C-suite audiences.

NVIDIA · NIMs · SDKs

• London
• Hybrid
• Permanent

Builds and optimizes the large-scale compute platform behind frontier AI, spanning bare-metal automation, Kubernetes scheduling, high-performance networking, storage, and fleet health. Engineers work across the stack, profiling training workloads, improving NCCL and collective communication, and creating tooling that makes heterogeneous clusters reliable and usable.

Kubernetes · NCCL · RDMA +3

• Oxford
• £21,805 pa
• Entry level
• Contract

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.

Data Centres

• London
• Hybrid
• Permanent

Work at the interface between frontier generative models and pharmaceutical/biotech customers, deploying, adapting and fine-tuning models in customer environments. Build production-grade API integrations, model-serving infrastructure and ML data pipelines, while acting as technical point of contact for partners. Combines deep ML research with customer-facing delivery in an interdisciplinary team.

AlphaFold · NeurIPS · ICML +1

• Cambridge
• Hybrid
• Senior

Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, building high-performance runtime and compiler components for end-to-end inference. Involves mapping large-scale neural network workloads onto future hardware, working with LLVM/MLIR, and collaborating with hardware architects on codesign. Hybrid role based in Cambridge.

LLVM · MLIR · TensorFlow +3

• Belfast
• On-site
• £42,972 – £51,270 pa
• Mid-level
• Contract

Conducts research in hardware-accelerated custom computing within QUB's Centre for Secure Information Technology, contributing to the European RIGOLETTO initiative on an open RISC-V automotive hardware platform for software-defined vehicles. Involves FPGA design, CPU architecture work, and collaboration with academic and industrial partners.

FPGA · RISC-V

• London
• Remote
• £75,000 – £105,000 pa
• Senior

Builds and deploys production LLM and Generative AI applications for enterprise clients, including RAG solutions, scalable data pipelines and AI-powered services. Works in a collaborative consultancy team of engineers and architects, applying software engineering best practices to take AI from proof of concept into production, with monitoring and optimisation of live systems.

Databricks · MLflow · LangChain +5

• London
• Manages people
• Permanent

Join the Preparedness team to anticipate and mitigate loss-of-control risks from increasingly capable AI systems, potentially culminating in recursive self-improvement. The role spans scalable oversight, automated auditing, monitorability testing, model behaviour science, and coordination mechanisms, alternating between hypothesis-driven research and building interventions that affect production models.