210 jobs within 10 miles of London
Faculty · 51–200 people · Series B
Lead the scientific direction and architectural rigour of upstream AI safety and evaluation standards, partnering directly with Frontier Labs. Design novel experiment frameworks, mentor technical teams, and bridge deep research with client strategy across high-stakes engagements.
NumPy · Pandas · Inspect AI +1
Wayve · 11–50 people · Series A
Builds and evolves the data pipeline and orchestration platform behind Wayve's autonomous driving data, revamping the existing Harness system and creating a new DAG-based workflow platform. Works on Kubernetes-deployed, distributed infrastructure handling hundreds of parallel pipeline steps, batch inference and evaluation workflows, closely with partner teams.
Harness · Airflow · Dagster +7
Wayve · 11–50 people · Series A
Train, debug and improve computer vision and 3D perception models for driver assistance, working across the full ML lifecycle from data and training to evaluation and iteration. The role spans latency-constrained on-car perception and large-scale offline work with lidar, maps and extra compute, building auto-labelling pipelines that feed a data flywheel.
LiDAR
OpenAI
Senior technical owner for a named portfolio of enterprise customers, acting as the "CTO of your book of business" and shaping AI strategy from pre-sales discovery through production adoption. Owns technical account plans across ChatGPT Enterprise, the OpenAI API, Codex and agentic solutions, leading discovery, architectures, evaluations and proofs of value while coordinating deployment, enablement and partner specialists.
ChatGPT Enterprise · OpenAI API · Codex +1
OpenAI
Lead end-to-end deployments of frontier models for strategic customers, owning discovery, scoping, system design, build and production rollout. Build full-stack systems in Python or JavaScript, embed with customer teams and feed field insights back into product and research roadmaps. Hybrid London role with up to 50% travel and Spanish-speaking customers.
OpenAI
Wayve · 11–50 people · Series A
Owns the autonomy performance measurement framework for a public-scale robotaxi deployment, defining metrics, dashboards and release gates for an end-to-end learned driving system with no existing playbook. Runs the detect-triage-root-cause-fix loop across model, robot software, backend and evaluation tooling, leading cross-functional teams without direct authority while staying hands-on in Python, C++ and SQL.
Databricks · Looker · Grafana +2
Wayve · 11–50 people · Series A
Lead large-scale data enrichment and curation for the Core Model Safety team, collaborating across pre/mid-training, reward modelling and self-supervised labelling. Build workflows for hard and rare event mining, design out-of-distribution detection for driverless operation, and improve ML operations efficiency across model engineering, infrastructure and compute.
PyTorch · CUDA · VLM +1
Wayve · 11–50 people · Series A
Builds and maintains core C++/Python components that interface self-driving models with vehicle and embedded systems, plus infrastructure to run and test autonomy capabilities. Owns reliability and performance of Linux-based systems and specialises in one domain such as localisation/mapping, filtering/diagnostics or control/inference, in a team scaling to 5-6 engineers.
Linux
Wayve · 11–50 people · Series A
Cross-functional individual contributor defining software architecture across onboard software, AI, simulation, training, inference and Robotaxi systems. Leads large architectural changes spanning multiple engineering organisations, setting boundaries and interfaces between AI, compute and vehicle systems, and acts as technical tiebreaker on complex decisions.
Wayve · 11–50 people · Series A
Set the technical direction for a petabyte-scale object storage platform underpinning autonomous driving AI, leading a multi-quarter programme from architecture through 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.
Kubernetes · Terraform · Azure Blob +3
Wayve · 11–50 people · Series A
Join a small, high-autonomy team building Wayve's Data Transfer Hub, mission-critical infrastructure moving petabytes of sensor data per day from global partners like Uber, Stellantis and Nissan. You'll design and operate large-scale pipelines in Python and Terraform, using Flyte, Kafka and Azure, with ownership of production systems and an out-of-hours on-call rotation.
Flyte · Kafka · Azure +4
Wayve · 11–50 people · Series A
Builds reusable Python libraries and platform tooling for multimodal data loading, distributed training, inference, checkpointing and observability, supporting ML teams running models across thousands of GPUs. Partners closely with researchers to turn complex workflows into stable, scalable software, leading projects from discovery to delivery. A software and platform engineering role rather than ML modelling.
PyTorch · TensorFlow · Azure +3
Wayve · 11–50 people · Series A
Build and operate backend services, APIs and data-processing workflows for a platform that deploys, runs and evaluates ML models over petabytes of driving data and large GPU fleets. Work spans model-execution workflows, versioned outputs, annotation and dataset-catalogue features, plus reliability, performance and cost work across distributed, compute-intensive systems.
Flyte · Airflow · Dagster +7
Wayve · 11–50 people · Series A
Develops next-generation generative world models and planners such as GAIA, simulating complex driving environments for faster training and scalable deployment. Works across diffusion, transformer and hybrid architectures, optimising inference latency and building interactive models for reinforcement learning and safety evaluation. Involves setting technical direction, mentoring researchers and publishing at top venues.
PyTorch · GAIA · Transformer +1
Wayve · 11–50 people · Series A
Owns validation strategy for ADAS and L2 autonomy functions, translating product, safety and regulatory requirements into test scenarios, metrics, coverage and acceptance criteria. Works hands-on with Python evaluation pipelines, simulation and SQL data analysis, spanning simulated and physical test environments. Open at senior IC or manager level, coordinating with Product, Safety and Release stakeholders.
Python · SQL
