Research Engineer - New Grad (2027)

Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co.

We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions

About The Role And Team

We are looking for passionate early-career Research Engineers to join the Research Group at Applied Intuition. The mission of the group is to create cutting-edge technology enabling next-generation physical AI, with emphasis on the two most challenging applications reshaping our everyday life: end-to-end autonomous driving and robotic generalist. We have a group composed of leading experts from top institutions and companies, recognized for their exceptional academic and industry contributions, including eight Best Paper awards at premier conferences and journals such as CVPR and ICRA. Learn more at appliedintuition.com/research.

Supported by industry-leading tools and infra, researchers can access millions of miles of data from large fleets, and deploy methods they develop into various autonomous and robotic systems including self-driving cars/trucks, autonomous mining/construction machines, humanoid robots, and dexterous hands. In addition to your research contributions, you will contribute to and learn from best practices in the autonomy and robotics industries within our fast-paced and customer-focused culture. Improvements deployed to our system immediately help our customers with their programs and deliver value to our business.

This role is designed for recent PhD or MS graduates ready to translate strong academic research into shipped autonomy systems.

At Applied Intuition, You Will

• Collaborate with our ADAS stack engineering team to test and deploy end-to-end algorithms for mass production vehicles
• Collaborate with our simulation team to deploy data-driven generation algorithms for highly efficient and automated tools
• Conduct research on architecture design, robustness, safety, and language modality incorporation for our differentiable stack
• Work closely with Research Scientists and interns on high-quality research publications to submit to top-tier conferences

We’re Looking For Someone Who Has

• Hands-on experience in at least one of the following fields:
  • World-action foundation model, video/Gaussian generation, diffusion policy, multi-modal robot learning
  • VLA post-training, reinforcement learning
  • Physics-aware reconstruction, deformable simulation
• MSc or PhD in machine learning and computer vision with autonomy and robotics applications or closely related field, graduating by December 2026 or Summer 2027
• Passion for next-generation, scalable autonomy and robotics for real-world systems
• Strong engineering and research skills and the ability to work both independently and collaboratively on projects
• Technical experience in: Python, Pytorch, computer vision, robotics systems, and distributed machine learning model training
  

Nice To Have

• Industry experience on relevant topics (self-driving application preferred)
• Passion for building and shipping customer-focused software frameworks or tools

Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.

FOR US-BASED ROLES: Applied Intuition is committed to providing an accessible and inclusive application and interview experience to applicants who are disabled veterans and other applicants with disabilities or medical conditions. Reasonable accommodations are available, requesting an accommodation will not affect your candidacy in any way, and you are not required to disclose the nature of your disability or medical condition in order to make a request.

If you require an accommodation please contact View email address on ev.careers . We will work with you!

Compensation Range: $140K - $200K