Senior Software Engineer, Perception ML Data
Indexed description
Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides.
Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles.
With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected.
Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors.
About The Role
We’re a team of high-output generalists where ML and systems engineering converge to push autonomy performance forward. As a Perception ML Data Engineer, you’ll bridge machine learning innovation and autonomy infrastructure to ensure our models learn from the most relevant, diverse, and high-quality data. Your work will directly impact how autonomous systems understand rare scenarios, adapt to global geographies, and scale safely.
Design and advance systems that:
- Leverage VLMs to curate geographically diverse datasets matching real-world driving distributions
- Develop high fidelity synthetic data frameworks across sensor modalities
- Optimize ML-powered validation of data quality and model readiness
- High-Output Generalist: Work across autonomy, infrastructure, databases, simulation, and ML development, gaining domain knowledge in Robotics and ML.
- Robotics Expert: Build state of the art solutions for data discovery, auto-labeling, and synthetic generation/reconstruction in close collaboration with Infrastructure and Autonomy.
- Architect hybrid systems combining deep learning and classical algorithms for scalable data curation and annotation.
- Design frameworks to quantify synthetic data’s real-world fidelity and improve synthetic data rendering quality.
- Build tools that automatically surface data gaps impacting perception model performance.
- Collaborate with autonomy engineers to turn raw sensor streams into targeted training priorities – addressing critical gaps that limit perception and autonomy performance
- BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area.
- Experience:
- 4+ years of industry software engineering experience with Python fluency and C/C++ familiarity. Proven ability to lead cross-functional technical projects from design to completion.
- You possess practical experience in implementing ML solutions and enjoy integrating them into real-world systems. Your focus is on deploying impactful, integrated solutions rather than purely theoretical ML experimentation.
- Familiarity working with synthetic or autonomous driving data.
- Experience building ML systems for robotic applications
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