294 jobs
PhysicsX
Build and deploy customer-facing applications powered by physics AI models, working directly with customers, data scientists and ML engineers. Involves rapid prototyping, Python/FastAPI microservices, and cloud deployment with Kubernetes, Terraform and AWS/Azure, plus quarterly travel to customer sites.
FastAPI · Helm · Kubernetes +3
PhysicsX
Deliver high-fidelity multi-physics CFD simulations, from geometry clean-up and meshing to post-processing and validation against experimental data. Build parametric CAD models and automate simulation pipelines for design optimisation and DoE, generating datasets for machine learning surrogates. Partner directly with customers on-site and mentor junior colleagues.
Star-CCM+ · OpenFOAM · Fluent +4
ITOL Recruit
A 15-step online, self-paced AI traineeship covering Python, data fundamentals, machine learning, prompt engineering, RAG, and Hugging Face projects, ending with an AWS Certified Cloud Practitioner exam. It is a paid training course with a job guarantee rather than a direct employer role, offering tutor and recruitment support to place candidates into junior AI engineer positions.
Jupyter Notebooks · VS Code · Streamlit +6
ITOL Recruit
A 15-step online, self-paced AI traineeship covering Python, neural networks, LLMs, prompt engineering, RAG, machine learning with scikit-learn, and data ethics, ending with an oral exam and AWS Cloud Practitioner certification. It includes real-world projects such as a Streamlit car price app and a Hugging Face sentiment classifier, plus 1-to-1 tutor and recruitment support with a job guarantee.
Jupyter Notebooks · VS Code · Streamlit +6
Wayve · 11–50 people · Series A
Owns the end-to-end release cycle for autonomous-driving AI 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
Wayve · 11–50 people · Series A
Lead the technical architecture and roadmap for onboard localisation, designing and productionising state-estimation systems that fuse GNSS, IMU and wheel odometry for accurate vehicle pose estimates. The role spans algorithm design, prototyping, validation and deployment on real-time vehicle platforms, with hands-on technical leadership and mentorship across robotics, calibration, controls and sensor teams.
GTSAM · Ceres · g2o +7
ElevenLabs
Embedded with strategic customers, you design tailored technical architectures, build full-scale integrations and take end-to-end ownership of high-impact projects. Working daily with customer engineers and executives, you use Python and API integration skills to solve complex problems. Remote-first across the UK, with a London office option and regular customer travel.
ElevenLabs
ElevenLabs
Owns the data infrastructure behind frontier AI models, building large-scale pipelines for collecting, filtering and transforming training datasets. Also trains classifiers, quality filters and labeling models, and designs curation strategies like deduplication and quality scoring. Builds tooling so researchers can explore and train on massive datasets quickly.
Kubernetes
Wayve · 11–50 people · Series A
Develops, tunes and validates trajectory-generation and motion-control algorithms that turn the AI Driver's outputs into safe, smooth vehicle motion across multiple platforms. Owns production-quality, latency-sensitive C++ control software through the full lifecycle, using simulation, closed-loop evaluation and on-road testing to characterise controller behaviour and track comfort, tracking-error and safety KPIs.
CAN
Wayve · 11–50 people · Series A
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. Requires deep safety-case and systems engineering expertise in safety-critical domains.
ISO 26262 · ISO 21448 · ISO/PAS 8800 +2
Wayve · 11–50 people · Series A
Owns shared onboard runtime foundations for autonomous vehicles: application frameworks, communication middleware, lifecycle management, health monitoring and observability. Day to day involves C++ development, end-to-end latency and performance profiling across OS scheduling, memory hierarchy and thread synchronisation, plus porting the stack to new operating systems and compute platforms.
NVIDIA Nsight · Lumos · tegrastat +5
Wayve · 11–50 people · Series A
You'll design, build and operate shared infrastructure for model access, agent runtimes and observability, taking projects from problem definition through technical design, deployment and ongoing operation. Working with security, IT and engineering teams, you'll create governed access layers, reusable tooling and standards so teams can run AI agents in production without one-off infrastructure.
Kubernetes · MCP · RAG
Wayve · 11–50 people · Series A
Develops and maintains Wayve's Core Simulation system in modern C++ and Python, integrating driving-stack components, simulated robot systems and vehicle-platform capabilities. Initially focused on high-scale open-loop evaluation, the role involves debugging on-road versus simulated behaviour, improving reproducibility, observability and automated testing, and profiling simulator performance across a shared codebase.
GenAI Development Tools
Wayve · 11–50 people · Series A
Owns the end-to-end architecture and technical roadmap for Remote Assistance, the real-time bridge between Wayve's AI Driver and human operators, spanning onboard vehicle integration, offboard services and operator HMI. Defines the vehicle-operator contract, fallback/MRM behaviour and latency budgets, and leads cross-org execution across autonomy, safety, platform and product teams to support L4 operation.
HMI
Wayve · 11–50 people · Series A
Sets technical strategy and roadmap for fault detection and fallback systems in an autonomous driving stack, designing and training detection mechanisms for robust driverless operation. Leads integration into the shared driving stack, aligning ML, inference optimisation and software teams, and mentors through architecture reviews. Works with large-scale training and fleet data in a small, high-impact team.
