Machine Learning Research Scientist, Accelerating Innovation
3 weeks ago
Nuro is a pioneering robotics company dedicated to improving everyday life through cutting-edge technology. Founded in 2016, Nuro has spent years developing and commercializing autonomous driving (AD) solutions. Our flagship product, the Nuro Driver, combines AD hardware with advanced AI-first self-driving software, built to learn and improve through data.
Backed by over $2 billion in funding from top investors, including Fidelity, Bailie Gifford, and Google, we've partnered with renowned brands like Uber, FedEx, Domino's, Walmart, Kroger, and 7-Eleven. Our mission is to revolutionize transportation and logistics using machine learning and robotics.
About the RoleWe're seeking a highly skilled Machine Learning Research Scientist to join our Learned Behavior team. As a key member of this team, you'll leverage cutting-edge ML techniques to accelerate software progress and solve real-world problems. Your focus will be on developing innovative strategies in active learning, data curation, and quality research to enhance our core behavior prediction, planning, foundation models, LLMs, and VLMs.
Key responsibilities include:
- Developing and implementing novel active learning methods to refine data selection, filtering, and mixing strategies.
- Leading initiatives to improve data quality, detect anomalies, and manage out-of-distribution examples.
- Collaborating with autonomy teams to build effective and efficient ML data pipelines and processes.
- Experimenting quickly, failing fast, and publishing success stories.
- Working with data collection and labeling teams to set a high-quality bar for incoming data.
To excel in this role, you should have:
- 3+ years of experience working with machine learning using deep networks and large volumes of data.
- Subject matter expertise and research in areas like Machine Learning, Deep Learning, Robotics, and state-of-the-art ML for autonomous driving and data utilization.
- Strong problem-solving and programming skills in C++ and Python.
- Expertise in at least one of the following domains: Active learning, curriculum learning, model uncertainty, density estimation, anomaly detection, or data selection and quality research for LLMs and VLMs.
- An M.Sc. or Ph.D. focusing on Computer Science, Artificial Intelligence, Mathematics, or a closely related field.
- Demonstrated research publications in major conferences (RSS, ICRA, CoRL, CVPR, ICLR, ICML, NeurIPS, ICCV, AAAI).
We offer a competitive total compensation package, including an annual base salary of $167,200 - $250,800, depending on experience and qualifications. You'll also be eligible for an annual performance bonus, equity, and a comprehensive benefits package.
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