Top Tech Jobs & Startup Jobs

Develop and optimize learning-based robotic manipulation and locomotion systems. Build low-latency teleoperation infrastructure, train reinforcement and imitation learning policies, deploy policies to real robots, diagnose control-pipeline bottlenecks, and reduce the simulation-to-real-world gap through simulation and hardware co-optimization.

Own Quadrants, an open-source Python compiler for performance-critical numerical computing. Responsibilities include API design, intermediate representation and lowering, multi-backend support, compiler optimization, GPU kernel development, numerical primitives, benchmarking, regression tracking, and roadmap ownership. The role combines GPU programming, compiler engineering, Python API design, performance optimization, user engagement, and open-source product direction, with potential to lead a small team.

Lead complex customer deployments of physical AI and robotics systems from prototype through production. Coordinate software, AI, hardware, infrastructure, operations, and customer teams; manage milestones, dependencies, site readiness, testing, validation, logistics, launches, risks, and technical blockers. Partner with enterprise customers, establish scalable deployment and release processes, and define approaches for scaling systems across diverse environments.

Design and optimize embedded control stacks for general-purpose robots, including motion planning, trajectory optimization, state estimation, and nonlinear optimal control. Build simulation-to-hardware software frameworks, integrate sensors and actuators, and debug and validate controllers on physical robots. The role requires production-grade C++ expertise, advanced robotics and control knowledge, and the ability to deliver reliable end-to-end robotic systems.

Designs and maintains foundational frameworks, internal tools, and reusable systems that accelerate AI research and engineering workflows. Collaborates across teams to validate use cases, simplify complex requirements, improve development processes, and reduce organizational friction. Responsibilities include identifying code design flaws, implementing large-scale changes, conducting code reviews, documenting practices, training teams, and maintaining high software quality.

Develop and ship production-ready physics simulation capabilities for Genesis-World, improving speed, fidelity, scalability, completeness, and solver coupling. Implement physics algorithms in Python using the Quadrants compiler across CPU and GPU backends. Validate methods through analytical solutions, cross-engine comparisons, and real-world data while supporting robotics and physical AI pipelines.

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 software engineering backbone of Genesis-World, an open-source multi-physics robotics simulation platform. Responsibilities include scalable testing for JIT-compiled systems, deterministic simulation replay, autodiff integration, scene editing, plugin architecture, actuation, local time stepping, event systems, serialization, telemetry, performance improvements, and legacy refactoring. The role also involves code reviews, issue triage, contributor support, and collaboration with compiler and physics teams across GPU and operating-system platforms.

Develop and ship production-ready physics simulation capabilities for Genesis-World, improving speed, fidelity, completeness, versatility, and scalability. Implement and optimize multi-physics algorithms, constraint solvers, adaptive timesteps, contact resolution, and heterogeneous solver coupling using Python and GPU/CPU backends. Validate methods through analytical solutions, cross-engine comparisons, and real-world data, while delivering tested, documented code for robotics learning pipelines.