Machine Learning Jobs

• 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

• London
• Hybrid
• Mid-level · manages people
• Permanent

Lead the Platform Integration team within Robot Software, owning early vehicle software integration, drive-by-wire and vehicle-facing drivers. You'll manage and grow engineers, set roadmap and priorities, and drive repeatable bring-up, validation and handover of new vehicle variants across OEM programmes.

CAN · Automotive Ethernet

• London
• Hybrid · 3 days in office
• Lead

Drive DMPK strategy across drug discovery projects, designing screening cascades and mechanistic experiments with an AI-first approach. Integrate DMPK, PD and toxicology data to predict human dose and safety windows, and author regulatory documents. Work closely with Chemistry, Pharmacology and AI/ML platform teams on multiple modalities including biologics and peptides.

R · Python · KNIME

• 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
• Mid-level
• Permanent

Builds and operates the CI/CD infrastructure underpinning Wayve's software development lifecycle, maintaining pipelines, build agents, runners and artifact storage. Works with engineering teams to cut build and test feedback times, improving caching, dependency management and reproducible builds. Also develops self-service tooling and automation to scale the build platform.

GitHub Actions · GitLab CI · Jenkins +2

• London
• Hybrid
• Senior
• Permanent

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

• London
• Hybrid
• Senior · manages people
• Permanent

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

• London
• Hybrid
• Senior
• Permanent

Owns the technical architecture and roadmap for LiDAR and cross-sensor 3D sensing, leading development of target-based and targetless calibration, LiDAR-to-camera alignment, temporal synchronisation and motion compensation. A senior individual-contributor role combining algorithm development, evaluation and production deployment with technical leadership and mentorship across the 3D sensing stack.

GTSAM · Ceres Solver · g2o +1

• London
• Hybrid
• Senior
• Permanent

Lead functional safety activities for an end-to-end autonomous driving system, building Item Definitions, running HARA/FMEA/FTA analyses, and shaping safety concepts and architectures across vehicle platforms and third-party safety-critical systems. Define verification and validation, including vehicle-level testing, and construct structured safety cases with claims, arguments and evidence to support certification.

ISO 26262 · SOTIF

• London
• Hybrid
• Senior
• Permanent

Owns the engineering release process for autonomous driving models, defining branching strategies, release cadence, configuration management and quality gates. Reviews model, architecture and code changes against intended outcomes, assesses evaluation results for safety and performance, and builds CI/CD tooling with PyTorch, TensorRT and GitHub Actions. Works across ML engineering, AI Platform, evaluation and product to unblock delivery bottlenecks.

PyTorch · TensorRT · GitHub Actions +1

• London
• Hybrid
• Lead · manages people
• Permanent

Lead a dedicated Runtime Platform team building the application frameworks, middleware, IPC, performance and observability foundations that support Wayve's onboard AI Driver. The role is people-first, combining coaching, hiring and roadmap ownership with technical direction across latency, profiling, real-time scheduling and embedded Linux, partnering with vehicle software, hardware and OEM programme teams.

QNX · OpenTelemetry · Grafana +7

• London
• Hybrid
• Mid-level
• Permanent

Develops embedded software connecting an AI Driver to vehicle steering, braking and propulsion systems, working with MATLAB/Simulink, CAN/CAN-FD tooling and vehicle ECUs. Involves bench and in-vehicle testing, drive-by-wire bring-up, OTA updates and ADAS/HMI interfaces alongside OEMs and suppliers.

MATLAB · Simulink · CANoe +4

• London
• Hybrid
• Senior · manages people
• Permanent

Own the technical vision and architecture for a petabyte-scale data enrichment platform that lets model engineers deploy, evaluate and improve ML models across large GPU fleets. Combine hands-on Python backend engineering with cross-team technical leadership, mentoring senior engineers and leading a small team of 2-3.

Flyte · Airflow · Dagster +6

• London
• Hybrid
• Permanent

Develop, integrate and validate control, trajectory-generation and action-processing algorithms that translate AI Driver outputs into safe, smooth vehicle motion across multiple platforms. Own production-quality, latency-sensitive C++ control software, using simulation, closed-loop evaluation and on-road testing to characterise controller behaviour and track comfort, tracking-error and safety KPIs.

CAN

• London
• Hybrid
• Director
• Permanent

Owns the architecture, strategy and integrity of safety cases for robotaxi and OEM ADAS products, defining top-level claims, argumentation structures and evidence traceability. Sits independently from Engineering and Product, providing expert challenge and oversight across AI/ML, systems, validation and operational safety. Focuses on safety arguments for AI-enabled autonomous driving, including functional safety, SOTIF and post-deployment monitoring.

ISO 26262 · ISO 21448 · ISO/PAS 8800 +2