Research Engineer - Training Platform

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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401(k) match

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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

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

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Research Engineer - Training Platform Mountain View, Mountain View,, California, United States At Rhoda AI, we're building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $400M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality. We're looking for a Research Engineer to build and maintain the training platform that powers our model development - experiment orchestration, job management, observability, and the tooling that lets researchers move from idea to result as fast as possible. What You'll Do - Build and maintain training orchestration systems for large-scale distributed model training across GPU clusters - Develop experiment management tooling: job configuration, tracking, reproducibility, and artifact management - Build observability infrastructure for training runs: loss curves, compute utilization, gradient statistics, and anomaly detection - Optimize and automate the research iteration loop from experiment launch to results analysis - Manage job scheduling and cluster utilization for efficient use of GPU compute - Build internal tooling and interfaces that help researchers move faster - Collaborate with training systems, data infrastructure, and research teams to support their platform needs What We're Looking For - Strong software engineering skills with experience

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