Jobs at Genesis

Lead customer robot deployments from workflow discovery and site assessment through scoping, financial modeling, technical alignment, execution, acceptance testing, training, and handoff. Partner with engineering, research, safety, solution engineering, customers, and external teams to define requirements, success metrics, dependencies, and milestones. Translate field feedback into deployment practices while managing scope changes, implementation tradeoffs, customer value, utilization, and support needs.

Owns the technical path from customer use cases to reliable robot deployments. Responsibilities include assessing automation feasibility, defining requirements and success metrics, designing integrations across robotics hardware, software, tooling, and customer systems, configuring and debugging systems onsite, and improving deployment tools and playbooks. The role partners with research and engineering teams to resolve field failures and requires customer communication, hands-on troubleshooting, and travel to deployment sites.

Build and manage a production supplier base for robotic hardware, including sourcing, qualification, dual sourcing, commercial negotiations, capacity planning, BOM and cost control, supplier quality, logistics, and MRP systems. Ensure clear-to-build readiness, inventory accuracy, supplier performance, and production support while developing domestic and international suppliers and leading cross-functional collaboration with engineering, manufacturing, quality, legal, and finance.

Annotate robot episodes, videos, images, and sensor data for robotics AI models. Label objects, actions, task steps, and outcomes; write behavioral descriptions; identify ambiguous cases; perform annotation quality checks; meet accuracy and throughput goals; and report tool or workflow issues to engineering. The role requires high attention to detail, strong written communication, sound judgment, and comfort working under deadlines and ambiguity.

Leads complex technical programs spanning AI research, robotics hardware, software, simulation, and foundation model training. Builds roadmaps, aligns Bay Area and Paris teams, manages dependencies and risks, establishes execution metrics, and automates program management workflows. Requires technical fluency across machine learning and hardware integration, strong communication, rapid domain learning, decisive execution, and ownership of outcomes.

Own the deployment-focused roadmap for Physical AI products, translating robotics research into reliable customer-facing solutions. Define release readiness criteria, success metrics, reliability thresholds, and scope. Coordinate research, robotics engineering, and field operations while supervising customer and partner pilots. Collaborate on robot, data collection, privacy, and infrastructure requirements, making product decisions amid technical ambiguity and incomplete information.

Build scalable infrastructure for robotics simulation, including workload management, environment frameworks, task interfaces, evaluation tooling, and real-to-sim pipelines. Collaborate with policy training and asset-generation teams to improve sim-to-real performance. The role requires extensive physics simulation expertise, particularly rigid body simulation or FEM, along with CUDA and GPU programming proficiency. Experience with robotics simulation platforms, synthetic data, asset pipelines, manipulation, humanoids, or embodied AI is advantageous.

Operate robots through teleoperation equipment during onsite data collection sessions. Follow predefined tasks and standard operating procedures, monitor robot behavior, identify unsafe or unexpected activity, and maintain safety and consistency during repetitive sessions. Provide session feedback, remain focused for extended periods, and collaborate with operations staff and session leads. The role is hands-on and execution-focused, with technical setup and hardware maintenance handled by other teams.

Build and optimize distributed foundation-model training infrastructure across multi-node GPU clusters. Profile data pipelines, GPU kernels, memory, networking, and CPU/GPU workloads to improve convergence speed and utilization. Develop CUDA, cuDNN, Triton, and custom kernel solutions integrated with PyTorch. Create monitoring and debugging tools for large-scale training runs and diagnose performance issues.

Build and maintain the software engineering backbone of Genesis-World, an open-source robotics simulation platform. Responsibilities include scalable testing for JIT-compiled engines, deterministic reproduction and serialization, autodiff infrastructure, scene editing, extensible plugins, robot actuation, event systems, timing architecture, refactoring, performance optimization, and cross-platform debugging. The role also involves code review, issue triage, contributor support, and collaboration with compiler and physics teams.

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.