Machine Learning Jobs

• United Kingdom
• Hybrid
• Lead

Senior technical role architecting agentic AI systems for defence and security clients, acting as technical lead on complex projects and setting departmental technical direction. Involves hands-on engineering in Python, client-facing proposal work, mentoring engineers and conducting technical interviews. Requires SC security clearance and UK residency.

• United Kingdom
• Entry level

Graduate role in the Human-Machine Understanding group, working at the intersection of AI, cognitive science and human-machine interaction. You will contribute to an Intelligent Interfaces framework spanning multi-modal human sensing, human-centric contextual modelling and agentic workflows, supporting client projects from human subjects studies to technical prototypes. Requires Python and AI/ML frameworks such as PyTorch, with scope to explore HRI, affective computing and cognitive architectures.

PyTorch · ROS2

• Cambridge
• Hybrid
• Senior

Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, building high-performance runtime and compiler components and mapping large-scale neural network workloads onto future hardware. Involves LLVM/MLIR work, graph transformations, scheduling and memory/layout optimizations, plus close collaboration with hardware architects on co-design.

LLVM · MLIR · TensorFlow +3

• United Kingdom
• Hybrid
• Senior

Develop algorithms and optimizations for NVIDIA's LPX inference and compiler stack, working at the intersection of large-scale systems, compilers, and deep learning. The role involves building high-performance runtime and compiler components, mapping inference workloads onto future hardware, and collaborating with hardware architects on codesign. Distinct focus on LLVM/MLIR, graph transformations, and spatial accelerators.

LLVM · MLIR · TensorFlow +3

• London
• Hybrid
• £165,000 – £190,000 pa
• Senior

Partner with founders and startup engineers as a technical advisor, guiding them from evaluation through deployment of LLM applications on the Claude Developer Platform. You'll run technical evaluations, design architectures, develop evaluation frameworks, and feed emerging use cases back to Product and Engineering, with travel to customer sites and events.

Claude · Claude Developer Platform

• London
• Hybrid · 1 day in office
• £325,000 – £485,000 pa
• Lead

Sets technical direction for agent-driven compute cluster lifecycle management, covering provisioning, updates and decommissioning across major clouds and own datacenters. Partners with security, research and cloud providers on secure-by-default, high-bandwidth, fault-tolerant clusters, and mentors engineers while owning multi-quarter strategy.

Kubernetes · Terraform · AWS +7

• London
• Hybrid · 3 days in office
• Senior
• Permanent

Senior technical owner for a portfolio of public sector customers, shaping AI strategy from pre-sales discovery through production adoption. Owns the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex and agentic solutions, designing architectures covering models, data, integration, security and governance while coordinating specialists across deployment, product and partners.

ChatGPT Enterprise · OpenAI API · Codex +1

• London
• Hybrid
• Lead · manages people
• Permanent

Lead and grow a London-based engineering team building real-time safety and oversight systems for AI agents, including the Auto-review platform that evaluates agent actions at permission boundaries. The role is a hands-on builder-manager position, setting technical direction while shaping architecture, reviewing designs, debugging, and writing code, working closely with alignment researchers and product teams.

OpenAI

• London
• Hybrid
• Lead
• Permanent

Lead an ambitious research agenda at the intersection of LLMs, VLMs, VLAs and embodied AI, exploring how world knowledge, memory and reasoning can drive better physical-world decisions. Stay hands-on developing architectures, training and post-training large-scale models, while mentoring researchers and shaping the team's technical direction across London and Sunnyvale.

PyTorch

• London
• Hybrid
• Senior
• Permanent

Owns the end-to-end release cycle for AI driving models, coordinating ML engineering, evaluation, data science, platform, testing and product teams. Defines release gates and promotion criteria from training through validation to fleet deployment, drives regression investigations and rollback decisions, and builds tooling and KPIs to remove bottlenecks in a non-deterministic ML environment.

GitHub · Buildkite · CLI

• Oxford
• Hybrid · 2–3 days in office
• Permanent

Field-facing role delivering autonomous vehicle projects for industrial customers across ports, airports and yards, combining hands-on engineering at Culham with remote development and support. Involves workflow testing, stakeholder management and identifying process gaps, with domestic and international travel including the UAE.

Linux · Unix

• London
• Hybrid · 3 days in office
• Mid-level

Join the Compute Infrastructure team to keep a planet-scale GPU accelerator fleet healthy and efficient. You'll build observability and telemetry pipelines, automate recovery, hunt compute waste, and optimise accelerator utilisation for large-scale training and inference, working closely with ML infrastructure and research teams.

GCP · Kubernetes · Nvidia GPU +1

• London
• On-site
• Mid-level
• Permanent

Build a greenfield deep learning research stack for a centralised trading book, working in pod-like teams with shared capital and strategic influence. Focus is deep-learning-first: neural networks, transformers, LLM-driven research, multi-modal modelling, NLP and agentic/autonomous research systems, including LLM fine-tuning for regression and forecasting.

GPUs

• London
• On-site
• Mid-level
• Permanent

Build a greenfield research and trading platform from scratch within a pod-like team at a scaling prop trading firm, working on GPU-heavy distributed training and MapReduce-style systems. The role centres on Ray, Spark, Dask, Databricks/Anyscale and Kubernetes for ML clusters, with strong autonomy to shape direction early.

Ray · Spark · Dask +6

• London
• Hybrid · 3 days in office
• Lead

Builds and evolves a large-scale ML infrastructure platform that supports training and deploying novel models across vast compute and data pools. Works closely with engineering, research and product teams, and explores deploying agents to improve platform robustness. Requires strong Python and experience scaling complex systems, with ML or Kubernetes exposure a plus.

Kubernetes · Google Cloud Platform · GCP