8 months ago
Base Salary
$194k - $291k/yr
Responsibilities
- Design and advance systems that use VLMs to curate geographically diverse datasets aligned with real-world driving distributions.
- Develop high-fidelity synthetic data frameworks across sensor modalities.
- Optimize ML-powered validation of data quality and model readiness.
- Architect hybrid systems combining deep learning and classical algorithms for scalable data curation and annotation.
- Measure and improve the real-world fidelity and rendering quality of synthetic data.
- Build tools that automatically identify data gaps affecting perception-model performance.
- Collaborate with autonomy engineers to transform raw sensor streams into targeted training priorities.
Requirements
- Bachelor’s degree in Computer Science, Robotics, Statistics, Physics, Mathematics, or another quantitative area.
- At least four years of industry software engineering experience.
- Fluency in Python and familiarity with C/C++.
- Ability to lead cross-functional technical projects from design through completion.
- Practical experience implementing ML solutions and integrating them into real-world systems.
- Familiarity with synthetic or autonomous-driving data is preferred.
- Experience building ML systems for robotic applications is preferred.
Benefits
- Annual performance bonus, equity, and a competitive benefits package.
Categories
ML EngineeringRobotics
About Nuro
Nuro builds the Nuro Driver, a Level 4 self-driving platform for robotaxis, commercial fleets, and personally owned vehicles. It licenses its autonomy software and integrates it with automotive-grade hardware for automakers and mobility platforms. Founded in 2016 and headquartered in Mountain View, California, Nuro is privately held and has operated real-world self-driving deployments.