Behavior & Planning (ML Research) Intern

Posted Yesterday
Be an Early Applicant
3 Locations
Hybrid
47-65 Hourly
Internship
Automotive
The Role
Develop behavior prediction and motion-planning models for autonomous vehicles using imitation learning, reinforcement learning, and classical planning. Formulate driving-behavior challenges as machine-learning or optimization problems, evaluate safety and progress tradeoffs, work with large-scale autonomy datasets, and present project updates with mentorship. The role involves PyTorch model development, uncertainty reasoning, distribution-shift awareness, and potentially constrained optimization, preference tuning, or interactive learning.
Summary Generated by Built In

Who we are

Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.

The Aurora Driver will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.

At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech or follow us on LinkedIn.

 

What we are looking for

We're searching for Summer 2027 Behavior & Planning Interns. You'll work on how the Aurora Driver decides what to do — forecasting how other agents move, planning and selecting trajectories, and the imitation-learning/reinforcement-learning models behind motion planning.

In this role you will

  • Develop end-to-end planning or prediction models for the Aurora Driver using imitation learning, reinforcement learning, and/or classical motion planning

  • Formulate ambiguous driving-behavior problems as concrete ML or optimization problems

  • Reason about competing objectives (e.g. progress vs. safety) and uncertainty in your model design and evaluation

  • Work with autonomy/robotics-scale datasets and benchmarks, not just toy datasets

  • Present a project plan and regular progress updates to the team, working closely with a mentor

Required qualifications

  • Currently pursuing a Bachelors, Master's or PhD in Computer Science, Robotics, or a related field, with a research or ML focus

  • Strong ML foundations with hands-on experience in PyTorch, including custom dataloaders, architectures, and loss functions

  • Some exposure to imitation learning, reinforcement learning, or motion planning

  • Experience training models on large-scale, non-toy datasets or benchmarks

  • Ability to reason mathematically about optimization objectives

  • Awareness of the compounding-error / distribution-shift problem in imitation learning

Desirable qualifications

  • Publication record at a peer-reviewed venue

  • Experience with constrained optimization or preference tuning (e.g. RLHF, DPO)

  • Experience with online reinforcement learning or interactive learning (e.g. DAgger)

Compensation

The hourly pay rate for this internship in Mountain View or San Francisco is:

  • $52.00 per hour for interns pursuing a bachelor’s degree;

  • $58.00 per hour for interns pursuing a master’s degree; and

  • $65.00 per hour for interns pursuing a doctoral degree.

The hourly pay rate for this internship in Pittsburgh is:

  • $47.00 per hour for interns pursuing a bachelor’s degree;

  • $52.00 per hour for interns pursuing a master’s degree; and

  • $58.00 per hour for interns pursuing a doctoral degree.

Working at Aurora

At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks.

We believe in-person work increases collaboration, empathy, and our ability to lead effectively. As a result, Aurorans are expected to work from the office at least 3 days per week, with some roles requiring more frequent in-office presence, up to 5 days per week, based on operational needs.

Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom.

Our commitment to safety

At the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at Aurora has a role in contributing to safety, every step of the way. Aurora expects commitment to our safety policies from every employee, and seeks candidates who take an active responsibility, can contribute to building an atmosphere of trust, and invest in the organization’s long-term success by prioritizing working safely, no matter what.

Our commitment to inclusion

Aurora considers candidates without regard to their race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, pregnancy status, parent or caregiver status, ancestry, political affiliation, veteran and/or military status, physical or mental disability, or any other status protected by federal or state law. Aurora considers qualified applicants with criminal histories, consistent with applicable federal, state, and local law. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at [email protected].

For California applicants, information collected and processed as part of your application and any job applications you choose to submit is subject to Aurora’s California Employment Privacy Policy.

Skills Required

  • Currently pursuing a Bachelor's, Master's, or PhD in Computer Science, Robotics, or a related field with a research or machine-learning focus
  • Strong machine-learning foundations and hands-on PyTorch experience, including custom dataloaders, architectures, and loss functions
  • Exposure to imitation learning, reinforcement learning, or motion planning
  • Experience training models on large-scale, non-toy datasets or benchmarks
  • Ability to reason mathematically about optimization objectives
  • Awareness of compounding error and distribution shift in imitation learning
  • Publication record at a peer-reviewed venue
  • Experience with constrained optimization or preference tuning, such as RLHF or DPO
  • Experience with online reinforcement learning or interactive learning, such as DAgger

Aurora Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Aurora and has not been reviewed or approved by Aurora.

  • Healthcare Strength — A broad set of medical plan options with dental and vision, plus company‑paid life and disability, signals strong healthcare support. Mental wellness access, including coaching and therapy sessions, further strengthens the offering.
  • Leave & Time Off Breadth — Flexible vacation for salaried employees, 12 paid holidays, and reasonable sick time indicate generous time‑off provisions. Some roles also accrue substantial vacation days annually.
  • Parental & Family Support — Paid parental leave and family‑forming reimbursement demonstrate meaningful support for growing families. Coverage for adoption, surrogacy, egg freezing, and genetic testing extends support beyond standard plans.

Aurora Insights

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The Company
HQ: Mountain View, CA
1,579 Employees
Year Founded: 2017

What We Do

Founded in 2017 by experts in the self-driving industry, Aurora is on a mission to deliver the benefits of self-driving technology safely, quickly, and broadly. To move both people and goods, the company is building the Aurora Driver, a platform that brings together software, hardware and data services to autonomously operate passenger vehicles, light commercial vehicles, and heavy-duty trucks. Aurora is backed by Sequoia Capital, Baillie Gifford, funds and accounts advised by T. Rowe Price Associates, among others, and is partnered with industry leaders including Toyota, Uber, Volvo, and PACCAR. Aurora tests its vehicles in the Bay Area, Pittsburgh, and Dallas. The company has offices in those areas as well as in Bozeman, MT; Seattle, WA; Louisville, CO; and Wixom, MI. To learn more, visit aurora.tech. Aurora is backed by Amazon and Sequoia, among others, and has partnerships with leading transportation companies including PACCAR, Uber, FCA, and Hyundai Group. It tests its vehicles in the Bay Area, Pittsburgh, and Dallas and has offices in those cities as well as in Bozeman, Seattle, Denver, and Detroit. Aurora hires people who want to build the future of transportation. Join us!

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