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Research Engineer, Robotics

Meta

Redmond, WA

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JOB DETAILS
SKILLS
Algorithms, Architectural Services, Artificial Intelligence (AI), C++ Programming Language, CUDA (Compute Unified Device Architecture), Computer Engineering, Computer Graphics, Computer Science, Data Sets, Emerging Technology, GPU (Graphics Processing Unit), Geometry, Graphics, High Throughput, Integrated Circuits (ICs), JAX (Java API for XML), Kernel Programming, Mathematics, Memory Hardware, Network Operations Center, Performance Tuning/Optimization, Physics, RGB Color Model, Ray Tracing, Realtime Programming, Research Laboratory, Risk Analysis, Robotics, Scientific Research, Shading, Simulation, System Integration (SI), Systems/Internals Programming
LOCATION
Redmond, WA
POSTED
6 days ago
**Summary:** Reality Labs Research (Reality Labs Research) brings together a multidisciplinary and highly interdisciplinary team of researchers and engineers to create the future of dexterous robotic manipulation. We are seeking a senior staff Research Engineer to design and build a custom CUDA-based compute renderer for robotics. You will own this end-to-end - architecting and implementing a novel GPU rendering system that serves as the visual backbone for robot learning at scale. This is a deeply technical, hands-on IC role for someone who has built rendering systems before. **Required Skills:** Research Engineer, Robotics Responsibilities: 1. Design and implement a custom compute renderer: Build a CUDA compute renderer supporting rasterization and ray tracing, optimized for high-throughput batch rendering on datacenter GPUs 2. Write high-performance GPU kernels: Develop and optimize kernels for core rendering operations including geometry processing, shading, light transport, and image synthesis 3. Produce ML-ready rendering outputs: Generate rendering outputs (RGB, depth, segmentation) suitable for direct consumption by ML training pipelines 4. Integrate into policy and training pipelines: Embed rendering capabilities into policy training loops, evaluation harnesses, and dataset generation workflows enabling end-to-end visual learning for robotic manipulation 5. Integrate with physics simulation: Render dynamic scenes including articulated rigid bodies, deformable objects, and skinned meshes in coordination with physics simulation systems 6. Collaborate on speed/quality tradeoffs: Partner closely with Research Scientists and ML Engineers to understand requirements and make principled tradeoffs between rendering fidelity and throughput 7. Own the full rendering stack: Maintain end-to-end ownership from scene ingestion through final image output, driving architectural decisions and performance optimization **Minimum Qualifications:** Minimum Qualifications: 8. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 9. Bachelor's degree in Computer Science, Computer Engineering, Physics, or Mathematics (or equivalent practical experience) 10. 10+ years of experience in GPU programming and real-time or offline computer graphics 11. Expert-level CUDA development including kernel optimization, GPU memory hierarchy, and performance tuning 12. Deep expertise in ray tracing and/or rasterization algorithms and their GPU implementations 13. Track record of building rendering systems or GPU compute pipelines 14. Experience with C++ and systems programming, including performance-critical codebases **Preferred Qualifications:** Preferred Qualifications: 15. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) 16. Master's or Ph.D. in Computer Science, Computer Graphics, Physics, or related field 17. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies 18. Experience with physically-based rendering, global illumination, or production rendering pipelines 19. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) 20. Familiarity with NVIDIA datacenter GPU architectures (Hopper, Blackwell) and how they differ from consumer GPUs for rendering workloads 21. Knowledge of robotics simulation or physics engines (MuJoCo, PhysX, Isaac Sim) 22. Experience integrating rendering systems into ML training pipelines (PyTorch, JAX) 23. Experience building renderers or graphics engines from scratch in a professional setting 24. Familiarity with OptiX, Vulkan, or custom ray tracing implementations on NVIDIA hardware **Public Compensation:** $219,000/year to $301,000/year + bonus + equity + benefits **Industry:** Internet **Equal Opportunity:** Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.

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Meta

INDUSTRY
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