Top Tech Jobs & Startup Jobs

Own Quadrants, an open-source Python compiler for performance-critical numerical computing and physics simulation. Lead its API, intermediate representation, lowering, compiler backends, optimization passes, numerical primitives, benchmarks, roadmap, and user adoption. Optimize GPU and CPU execution, maintain system coherence, track regressions, improve usability, and collaborate with Genesis users. The role combines compiler research, GPU engineering, API design, open-source product ownership, and future leadership of a small team.

Design, build, and scale security infrastructure across systems, networks, endpoints, and products. Own security architecture, detection/response, vulnerability and risk management, and security policies. Integrate security into the SDLC, partner with engineering, run incident response and monitoring, lead security education, and temporarily own IT infrastructure.

Develop, validate, and ship production-grade multi-physics simulation capabilities for Genesis-World. Improve speed, fidelity, completeness, versatility, and scalability across solvers and backends. Implement and validate algorithms end-to-end in Python/JIT-compiled kernels, optimize CPU/GPU performance, and ensure real-world and cross-engine consistency for robotics applications.

Lead ownership of Quadrants: design API, IR, lowering, backend support and optimization passes; implement numerical primitives; benchmark and track regressions; collaborate with Genesis users; prioritize usability while delivering high-performance GPU and CPU kernels. Grow into and potentially hire a small team.

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.

Lead end-to-end execution of complex customer deployments for physical AI and robotics systems. Coordinate cross-functional engineering, hardware, AI, infrastructure, and customer teams; manage milestones, site readiness, testing, validation, logistics, and launch. Engage enterprise customers, surface risks, resolve technical blockers, and build scalable deployment and onboarding processes.

Source and engage elite research scientists, software engineers, and robotics/infra talent using targeted channels (papers, GitHub, conferences). Build high-converting outreach, map markets, maintain pipelines, and operationalize scalable sourcing (Ashby, automation, enrichment). Measure response rates and pipeline health to iterate.

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.

Build and optimize low-latency on-device and distributed GPU inference pipelines. Implement and tune low-level CUDA/Triton kernels, optimize for throughput and latency, and develop monitoring/debugging tools to ensure reliable, deterministic inference in robotics and cluster environments.

Full-cycle technical recruiter focused on sourcing and closing elite Research Scientists, Software Engineers, and Robotics engineers. Partner with founders and technical leaders to design searches, build scalable sourcing and screening workflows (in Ashby), run a high-quality candidate experience, and automate recruiting processes to scale hiring.