Machine Learning Jobs

• London
• Hybrid
• Lead
• Permanent

Lead the technical architecture for integrating an autonomous driving AI platform with automotive OEM and Tier 1 vehicle systems, spanning sensors, middleware, ECU constraints, timing, diagnostics and safety. Own interface contracts, requirements processes and architecture decisions across customer programs, and represent the company in partner technical discussions.

CAN · FlexRay · Automotive Ethernet +2

• London
• Hybrid
• Lead
• Permanent

Lead the technical direction for an offline 3D reconstruction system that turns raw vehicle sensor data into quality-assessed 3D ground-truth geometry and ego motion. The role spans SLAM, lidar point-cloud registration, state estimation and sensor fusion, with responsibility for architecture, roadmaps, interfaces and cross-team alignment. It is a principal-level leadership position mentoring engineers and setting reconstruction quality standards.

ROS · PCL · OpenCV +3

• London
• Hybrid · 3 days in office
• Senior

Lead pharmacology and translational biology strategy for large molecule therapeutics, designing in vivo efficacy and complex in vitro functional assays. Act as Biology Lead on projects, coordinating internal workflows and external CROs through candidate selection, while feeding data back into generative AI design loops.

Machine Learning · AI · Computational Biology +1

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

Join a newly formed Scheduling team to own and extend systems that orchestrate compute allocation for complex ML workloads on Kubernetes. You'll design scheduling policies like gang scheduling and topology-aware placement, build custom Kubernetes controllers and CRDs, and partner with ML researchers to optimize GPU and TPU utilization.

Kubernetes · Kueue · Volcano +5

• London
• Hybrid
• Lead · manages people
• Permanent

Lead a small team iterating on Wayve's end-to-end L2 driving model, balancing hands-on Python coding and experiments with directing priorities. Diagnose on-road issues, root-cause them, and drive fixes through data recipes, model architecture, evaluation and release readiness, working across teams on model and vehicle interface problems.

Nissan · Mercedes

• London
• Hybrid
• Senior
• Permanent

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

• London
• Hybrid
• Senior
• Permanent

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

• London
• Hybrid
• Lead
• Permanent

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

• London
• Hybrid
• Senior
• Permanent

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

• London
• Hybrid
• Mid-level
• Permanent

Own a substantial work package end-to-end, defining the problem, setting strategy and sequencing work to ship outcomes for an end-to-end AI driving platform. Lead a cross-functional team of engineers, researchers and PMs without formal authority, translating R&D progress and customer needs into a product roadmap with clear KPIs and milestones.

• London
• Hybrid
• Lead
• Permanent

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.

• London
• Hybrid
• Senior
• Permanent

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

• London
• Hybrid
• Lead · manages people
• Permanent

Lead a London-based team building and operating large-scale multi-cloud, multi-region GPU compute and storage infrastructure for ML training and inference. The role is people-first: coaching engineers, hiring, and owning roadmap and delivery, while guiding Kubernetes scheduling, capacity planning and cost trade-offs across heterogeneous GPU fleets.

Kubernetes · Kueue · Nvidia Hopper +2

• London
• Hybrid
• Senior
• Permanent

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

• London
• Hybrid
• Permanent

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