Research Engineer, Robotics

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.

Responsibilities

• 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
• Write high-performance GPU kernels: Develop and optimize kernels for core rendering operations including geometry processing, shading, light transport, and image synthesis
• Produce ML-ready rendering outputs: Generate rendering outputs (RGB, depth, segmentation) suitable for direct consumption by ML training pipelines
• 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
• Integrate with physics simulation: Render dynamic scenes including articulated rigid bodies, deformable objects, and skinned meshes in coordination with physics simulation systems
• 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
• Own the full rendering stack: Maintain end-to-end ownership from scene ingestion through final image output, driving architectural decisions and performance optimization

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Bachelor's degree in Computer Science, Computer Engineering, Physics, or Mathematics (or equivalent practical experience)
• 10+ years of experience in GPU programming and real-time or offline computer graphics
• Expert-level CUDA development including kernel optimization, GPU memory hierarchy, and performance tuning
• Deep expertise in ray tracing and/or rasterization algorithms and their GPU implementations
• Track record of building rendering systems or GPU compute pipelines
• Experience with C++ and systems programming, including performance-critical codebases Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Master's or Ph.D. in Computer Science, Computer Graphics, Physics, or related field
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience with physically-based rendering, global illumination, or production rendering pipelines
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Familiarity with NVIDIA datacenter GPU architectures (Hopper, Blackwell) and how they differ from consumer GPUs for rendering workloads
• Knowledge of robotics simulation or physics engines (MuJoCo, PhysX, Isaac Sim)
• Experience integrating rendering systems into ML training pipelines (PyTorch, JAX)
• Experience building renderers or graphics engines from scratch in a professional setting
• Familiarity with OptiX, Vulkan, or custom ray tracing implementations on NVIDIA hardware