110 jobs
PhysicsX Singapore
Lead technical delivery of physics-informed AI, architecting deep learning models and optimisation methods to predict and control physical systems. Own data pipelines and pre-processing best practices while mentoring a team and collaborating with simulation engineers and customers. Involves frequent on-site customer travel across multiple regions.
PhysicsX Singapore
Lead the deployment of ML models and engineering surrogates—deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, and optimisation—into customer production environments. Own scoping, architecture, and success metrics for data/ML systems built with Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow across cloud and on-prem. Mentor engineers and data scientists while travelling 3-4 weeks per quarter to customer sites worldwide.
Faculty Remote (UK)
Lead backend and edge/IoT engineering for high-stakes Defence projects, bridging proof-of-concept work and robust production systems. You will mentor a squad of engineers, design complex components, and build CI/CD and containerisation pipelines with Docker and Kubernetes while shipping Python and compiled-language code alongside ML engineers and data scientists.
Wayve London
Owns the data strategy behind an end-to-end autonomous driving AI platform, spanning the full learning cycle from foundation model training to production programmes. Leads a multidisciplinary data organisation, deciding what data matters and building the flywheel from real-world signals through discovery, curation and enrichment. Focuses on finding rare, safety-critical scenarios in very large datasets using embeddings, semantic search and model-driven selection.
Wayve London
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 performance improvement loop across model, robot software, backend and evaluation tooling, leading cross-functional execution without direct reporting authority while staying hands-on in Python, C++ and SQL.
ElevenLabs United Kingdom
Owns large-scale distributed web crawling systems that discover, fetch and extract data from billions of pages to feed frontier AI models. Work spans content extraction from messy HTML, web-scale deduplication, recrawl and freshness strategies, politeness and rate limiting, plus tooling for researchers to request and explore crawled data.
Wayve London
Cross-organisational individual contributor defining software architecture as Wayve scales its AI Driver across vehicle platforms, OEM programmes and Robotaxi. Works at the intersection of AI, robotics, computer vision, simulation, training and inference, onboard software and product engineering, setting boundaries, interfaces and abstractions and leading large architectural changes across teams.
Wayve London
Lead the Applied Methods Data Science team, partnering with the Autonomy organisation to turn experimental and observational analysis of real and simulated driving into evaluations and insights. Set three-, six- and 12-month roadmaps, review technical proposals for statistical rigour, hire and grow data scientists, and build tooling to scale the team's capability.
Wayve London
Owns the technical architecture and roadmap for LiDAR and cross-sensor 3D sensing, developing calibration, registration, temporal alignment and motion compensation methods. Blends algorithm research with production deployment in C++/Python, providing technical leadership and mentorship across the 3D sensing stack.
Wayve London
Lead a newly dedicated Runtime Platform team building the application frameworks, middleware, IPC, performance and observability foundations that let Wayve's onboard AI Driver run in real time. 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.
Wayve London
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.
Wayve London
Lead large-scale training and post-training for Gaia, Wayve's world model that predicts future driving video and runs closed-loop with the driving stack. Own model architecture decisions, push autoregressive rollouts toward longer, more stable generation, and make the model deployment-ready. Partner with research, applications, simulation engineering and cloud teams, mentoring and setting technical direction.
Wayve London
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.
Wayve London
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.
Wayve London
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.
