Sensor Sim - ML Engineer
Location
Sunnyvale, California, United States
Compensation
$125k–$222k USD
Type
full time
Posted
1 months ago
Remote
Yes
Market range · company + function + seniority
$222k—$222k—$250k
p25 · target · p75 · n=12
Posted $222k · in the market band
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Job description
About Applied Intuition
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 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.
Meet our software engineers!
Meet some of our software engineers who are shaping the future of autonomy and delivering world-class solutions helping customers shorten time to market. Hear about what brought them to Applied Intuition, what’s kept them interested, and their advice to potential candidates.
About the role
We are looking for a software engineer to join our team working on the incorporation of modern machine learning approaches into production-grade sensor simulation. In this role you will work with our research team to apply state of the art approaches to model worlds and sensors such as Lidars, Radars and Cameras.
At Applied Intuition, you will:
- Drive research, development and deployment of generative and other machine learning techniques into our sensor simulator.
- Work closely with rendering and physics-based modeling teams to build novel approaches fusing the best of all techniques.
- Focus on projects with a clear path to production value and customer impact.
We're looking for someone who has:
- A Bachelor's degree in Computer Science, Software Engineering, or equivalent
- 5+ years of experience building software components or (sub) systems that address real-world machine learning challenges
- A passion for turning their domain expertise into tooling that boosts the productivity of teams working on various real-world applications of autonomous systems
- Hands-on experience with evaluation and optimization for large generative models
- Hands-on experience with agentic system design
- Deep understanding of machine learning foundations who can apply various techniques to new problems
- Understanding of 3D geometry, optical flow or video generation
Nice to have:
- Experience working with Generative World Models (Cosmos, UniSim, sora-style architectures)
- Experience with robotics simulation products (IssacSim, MuJoCo, Omniverse, USD)
- Experience with applying synthetic data to machine learning tasks
- Hands on experience with characterization of models for Lidar, Radar, and Camera
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.
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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