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Software Engineer - Machine Learning - job 1 of 2

About Applied Intuition

Applied Intuition is the vehicle intelligence company that accelerates the global adoption of safe, AI-driven machines. Founded in 2017, Applied Intuition delivers the ADAS/AD toolchain, Vehicle OS, and autonomy stack to help customers build intelligent systems, create next-generation experiences, and shorten time to market. 18 of the top 20 global automakers trust Applied Intuition’s solutions to drive the production of modern vehicles. Applied Intuition serves the automotive, trucking, construction, mining, agriculture, and defense industries and is headquartered in Mountain View, CA, with offices in San Diego, CA, Ft. Walton Beach, FL, Ann Arbor and Detroit, MI, Washington, D.C., Stuttgart, Munich, Stockholm, Seoul, and Tokyo. Learn more at appliedintuition.com.

We are an in-office company, and our expectation is that 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. (Note: For EpiSci job openings, fully remote work will be considered by exception.)

About the role

We are looking for a machine learning engineer with strong industry experience who is looking to implement and productionize cutting-edge research across our core product pillars. You will help position Applied Intuition as the most advanced vehicle software supplier to the largest OEMs in the world. You will work with a team of world-class software and machine learning engineers who are developing capabilities that will revolutionize the way that people interact with vehicles. At Applied Intuition, we encourage engineers to take ownership of technical and product decisions, interact closely with users to collect feedback, and contribute to a thoughtful, dynamic team culture.

At Applied Intuition, you will:

  • Leverage the latest advancements in machine learning to develop new systems for autonomy development workflows.
  • Work across our entire stack to develop new products, features, and tools for our end users.
  • Work closely with customers to identify additional areas across the product suite where AI/ML techniques can provide significant value.

We're looking for someone who has:

  • A Bachelor's degree in computer science, physics, robotics, or related fields from a top institution
  • 2+ years of experience working with ML techniques including but not limited to NLP, computer vision, reconstruction algorithms, image generation, or multi-modal models.

Nice to have:

  • Peer-reviewed research at machine learning conferences like NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV, IROS, or ICRA.
  • Experience building software for technical end users.
  • A Master’s degree or PhD in computer science, physics, robotics, or related fields

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $125,000 - $222,000 USD annually.

Candidates more specifically interested in perception roles can also apply here.

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.

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CEO of Applied Intuition
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Qasar Younis
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Average salary estimate

$173500 / YEARLY (est.)
min
max
$125000K
$222000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

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Applied Intuition equips engineering and product development teams with software that makes it faster, safer, and easier to bring autonomy to market.

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Full-time, hybrid
DATE POSTED
May 20, 2025

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