Top Tech Jobs & Startup Jobs in London

Own Quadrants, an open-source Python compiler for high-performance physics and numerical computing. Lead its API, IR, lowering, compiler optimizations, GPU and CPU backends, numerical primitives, benchmarks, and roadmap. Improve kernel performance, usability, correctness, and extensibility while partnering with Genesis users and the broader open-source community. The role combines GPU programming, compiler engineering, Python API design, performance analysis, and technical leadership, with potential to grow into managing a small team.

Design, build, and maintain petabyte-scale batch and streaming data pipelines for robotics foundation model training and evaluation. Own data models, storage systems, ingestion, transformation, and orchestration infrastructure. Standardize processing across teleoperation and synthetic simulation datasets while operating production-grade distributed systems and infrastructure.

Build and maintain the Genesis-World core engineering infrastructure to reduce friction for simulation: improve testing and JIT compile performance, enable bit-exact reproducibility, make autodiff efficient, support live scene editing and extensibility, improve actuation and time management, refactor core systems, and support community contributions and reviews.

Build a high-throughput GPU-based simulation pipeline for robotics foundation model training, implement actuators/sensors/controllers, bridge sim-to-real with policy training, and develop real-to-sim asset pipelines in collaboration with robotics and asset teams.

Lead profiling and performance ownership of a hybrid raster/ray-traced renderer. Profile, diagnose, and optimize GPU/CPU rendering across platforms, build custom instrumentation, evolve hybrid paths, set technical direction, mentor senior engineers, and collaborate with hardware vendors on low-level GPU issues.

Full-cycle recruiter responsible for sourcing and closing elite Research Scientists, Software Engineers, and Robotics engineers. Partner closely with founders and technical leaders, build scalable sourcing and screening workflows (Ashby/ATS), run a fast, candidate-friendly hiring process, and use data and automation to optimize pipeline health and conversions.

Lead development of a high-performance robotics simulation platform and compiler stack. Design compute infrastructure and dataflows for physics simulation and foundation-model training. Implement JIT/LLVM-based GPU codegen, optimize compile/runtime performance, add differentiable programming support, collaborate with simulation engineers, and contribute to open-source ML compiler projects.

Design and implement embedded control stacks, motion planning, and trajectory optimization for dynamic robots. Build real-time state-estimation pipelines fusing heterogeneous sensors, formulate and solve optimal control problems (nonlinear MPC, convex/trajectory optimization), create modular sim-to-hardware software, and lead on-robot debugging, tuning, and validation of controllers.

Develop and optimize a learning-based robotic manipulation control stack; design and maintain low-latency teleoperation systems; train and deploy policies using reinforcement and imitation learning; diagnose control-pipeline latency and sim-to-real gaps; co-optimize simulation and real-world robot behavior; collaborate on building general-purpose Physical AI.

Design, build, and optimize distributed PyTorch training systems for multi-node GPU clusters. Profile and eliminate performance bottlenecks across data pipelines, kernels, and networking. Implement low-level CUDA/cuDNN/Triton kernels, tune hardware-software interactions, and develop monitoring and debugging tools for large-scale training runs to maximize utilization and reduce time-to-convergence.