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Research Engineer, Robotics

Meta - Redmond, WA

Posted Jun 10, 2026

Benefits

Parental leave
Not verified
Non-birth-parent leave
Not verified
Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
Not verified
Relocation assistance
Not verified
Childcare support
Not verified
Learning budget
Not verified
Verification
Not verified checked Jun 7, 2026
Salary
$219K-$301K From the posting source checked Jun 20, 2026
401(k) match
Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

123% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Engineering From the posting source checked Jun 20, 2026
Seniority
Staff Plus From the posting source checked Jun 20, 2026

Schedule

Shift type
Not verified
Weekend work
Not verified

Company

Equity
Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter
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Assessment
Not verified
Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Research Engineer, Robotics Redmond, WA 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,

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