Machine Learning Jobs

• London
• Hybrid
• Lead
• Permanent

Lead large-scale training and post-training for Gaia, Wayve's world model that predicts future driving video frames and runs closed-loop with the driving model. Own model architecture and training-strategy decisions, push autoregressive generation toward longer, more stable rollouts, and make the model deployment-ready. Work across Research, Applications, Core Simulation Engineering and Cloud/Infrastructure, mentoring and setting technical direction.

PyTorch

• London
• Hybrid
• Senior
• Permanent

Set the technical strategy and roadmap for fault detection and fallback systems in an autonomous driving stack, designing and training detection mechanisms that enable safe driverless operation. Lead integration into the shared driving stack, working closely with machine learning, inference optimisation and software engineering partners, and mentor across teams. The role sits in a small, high-impact Core Model Safety team with access to large-scale training and fleet data.

• San Francisco, United States
• Hybrid
• US$150,000 – US$190,000 pa

Delivery-focused role embedding physics-aware AI models into customer tools, building reliable ML data pipelines and working with 3D point-cloud and mesh data. Spans data science and software engineering, translating R&D into reusable libraries and products, with regular on-site customer travel.

TensorFlow · MLflow · Spark +6

• New York, United States
• Hybrid
• US$150,000 – US$190,000 pa
• Mid-level

Builds and deploys machine learning systems for industrial physics challenges, designing reliable data pipelines and working with 3D point-cloud and mesh data. Partners directly with customers on-site to embed AI models into practical tools, translating R&D outputs into reusable libraries and products. Requires Python, cloud, and MLOps experience with frequent travel.

TensorFlow · MLflow · Spark +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

• London
• Hybrid · 3 days in office
• Senior

Join a newly formed LLM Engineering team to architect, implement and own systems bringing large language models into scientific and business processes. Work spans LLM serving stacks, agentic infrastructure, RAG, evaluation frameworks and fine-tuning, partnering with researchers to translate scientific needs into technical AI specifications.

vLLM · GCP · MCP

• London
• Hybrid · 1 day in office
• £325,000 – £395,000 pa
• Senior

Builds foundational infrastructure for AI safety, oversight and intervention, including data storage, metrics and evaluation systems, and tooling for human and agentic review. The role also involves running these systems day to day and building multi-layered, real-time defenses against misuse at scale.

Claude Code

• London
• Hybrid · 1 day in office
• £325,000 – £390,000 pa
• Senior

Lead and scope multi-month infrastructure projects, making architectural decisions for large-scale distributed systems that train and serve AI models. Work spans Kubernetes clusters, data pipelines, databases, observability and developer tooling, partnering with research and product teams while owning reliability, scalability and security.

Kubernetes · AWS · GCP +6

• Sydney, Australia
• Hybrid
• Mid-level
• Permanent

Design and deliver bespoke data science solutions for clients across government, finance, retail, energy and defence, mapping end-to-end approaches and software architecture. Act as a technical advisor, setting code and rigour standards for project teams while building scalable algorithms in Python, NumPy, Pandas and TensorFlow or PyTorch.

Python · NumPy · Pandas +3

• Sydney, Australia
• Hybrid
• Mid-level
• Permanent

Deliver bespoke, production-grade machine learning systems for clients across government, finance, retail, energy, life sciences and defence. The role spans building and deploying ML software and infrastructure, defining deployment standards, and leading technical scoping and architecture decisions while advising non-technical stakeholders. Work centres on Python, frameworks like Scikit-learn, TensorFlow or PyTorch, and cloud platforms with Docker and Kubernetes.

Scikit-learn · TensorFlow · PyTorch +5

• London
• Hybrid
• Permanent

Customer-facing technical role helping organisations evaluate, build, deploy and adopt AI technology. Work spans architecture, integrations, data, security and evaluation, plus demos, prototypes and production solutions, with enablement workshops and delivery coordination alongside Sales, Product, Research and Engineering. This is a general talent pool rather than a specific vacancy.

OpenAI

• Oxford
• Hybrid
• Senior
• Permanent

Full-stack engineer joining the Over-the-Air and Configuration team, building Python back-end services that deliver software and configuration from cloud to autonomous vehicle fleets. Work spans GCP infrastructure, Terraform, Mender, Linux on-vehicle systems, security and CI/CD, with front-end tooling built using AI-assisted development.

GCP · Terraform · Mender +5

• London
• Senior

Serve as the trusted technical ML and AI expert for enterprise customers, architecting production-grade ML and AI workloads on the Databricks Data Intelligence Platform. Specialise in GenAI solutions such as RAG architectures, agentic systems and AI observability, while mentoring colleagues and influencing the platform's AI roadmap.

Databricks · AWS · Azure +7

• London
• Mid-level
• Permanent

Own the science strategy for AI-powered brand safety and content classification, building LLM-driven multimodal systems that make billions of millisecond-latency decisions across web, mobile app, CTV and audio inventory. The role blends frontier research in adversarial ML, synthetic content detection and semantic understanding with large-scale production engineering, translating prototypes into deployed models and publishing at peer-reviewed venues.

Amazon DSP

• London
• Hybrid
• Senior
• Permanent

Builds data-intensive, AI-powered applications and infrastructure that help operators and investigators detect, triage and review high-severity harm, working across UIs, services and pipelines. Partners closely with the Child Safety team and cross-functional groups, owning systems end-to-end in an ambiguous, fast-moving environment.

Spark · Kafka · Flink +3