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Machine Learning Research Scientist - Prediction & Smart Agents

NuroMountain View, California (HQ)
On-site Full-time $193.9K/yr - $291.1K/yr

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Experience Level

Experience

Qualifications

We are seeking candidates with a strong background in machine learning and a passion for autonomous systems. Ideal candidates will have experience in:Machine learning model developmentGenerative sequence modelingTraffic prediction in autonomous vehiclesCollaboration within interdisciplinary teams

About the job

Who We Are

Nuro is at the forefront of self-driving technology, dedicated to making autonomy accessible for everyone. Founded in 2016, we are developing the most scalable autonomous driving system, merging advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed for various applications, including robotaxis, commercial fleets, and personal vehicles. With years of successful deployments, Nuro provides automakers and mobility platforms a clear pathway to commercial-scale autonomous vehicles, paving the way for a safer and more connected future.

About the Role

The Prediction team is tasked with leveraging cutting-edge machine learning techniques to enhance the functionality of the Nuro Driver. As a pivotal member of the Prediction and Smart Agents team, your role will center on developing state-of-the-art models that predict the behavior of surrounding traffic, which are integral to our autonomous systems. These models will be utilized both on-board and off-board in realistic closed-loop simulations.

In this position, you will delve into innovative machine learning approaches to address complex challenges in autonomous driving. Your work will involve employing generative sequence modeling techniques to accurately predict intricate, interactive traffic scenarios. This necessitates a deep understanding of the intentions of other road users and their impact on safe driving decisions. You will also explore diverse input modalities, including End-to-End (E2E) strategies, to forecast the behavior of other agents. A crucial aspect of this role is the creation of intelligent, controllable agents to facilitate effective closed-loop training within simulations.

If you are driven by the challenge of solving complex problems, leading impactful research, and witnessing your contributions in real-world applications, we invite you to apply!

About the Work

  • Design and develop scalable, machine learning-based prediction systems to generate multi-modal, realistic, and kinematically feasible trajectories.
  • Engage in pioneering research focused on generative sequence modeling and sequential decision-making, exploring areas such as:
    • Scalable generative sequence modeling techniques.
    • Modeling marginal, conditional, and joint distributions for interactive agents.
    • Transformer-based encoder-decoder frameworks.
    • Large generative models and diffusion techniques.
    • Agent controllability through conditioning, guidance, and various methodologies.
  • Collaborate closely with the Planning team to create realistic and controllable agents that enhance our simulation capabilities.

About Nuro

At Nuro, we are revolutionizing the future of transportation through the development of autonomous technology that is safe, efficient, and accessible. Our innovations are designed to seamlessly integrate into everyday life, transforming how we move goods and people.

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