AI Infrastructure Engineer - Autonomy

About Applied Intuition

Applied Intuition is the vehicle intelligence company that accelerates the global adoption of safe, AI-driven machines. Founded in 2017 and now valued at $15 billion following its recent Series F funding round, Applied Intuition delivers the Vehicle OS, Self-Driving System, and toolchain to help customers build intelligent vehicles and shorten time to market. 18 of the top 20 global automakers and major programs across the Department of Defense trust Applied Intuition's solutions to deliver vehicle intelligence.

Applied Intuition services the automotive, defense, trucking, construction, mining, and agriculture industries and is headquartered in Mountain View, CA, with offices in Washington, D.C., San Diego, CA, Ft. Walton Beach, FL, Ann Arbor, MI, London, Stuttgart, Munich, Stockholm, Bangalore, Seoul, and Tokyo. Learn more at

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.

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Note:

For Epi Sci job openings, fully remote work will be considered by exception.)

About the role

We are looking for both infrastructure engineers with expertise in machine learning pipelines and ML engineers that want to work beyond modeling to join our AI Infrastructure group. This role will work across the entire AI lifecycle (dataset generation, training frameworks, compute, evaluation, and deployment) and work directly with modeling teams. This team is a good fit if you are excited to work on broad, ambiguous problems and develop across the entire ML stack.

At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, closely interact with external and internal users to collect feedback, and contribute to a thoughtful, dynamic team culture.

At Applied Intuition, you will:

* Design and build training, inference, and evaluation infrastructure to support our current autonomy stack development, orchestrating massive GPU clusters to process petabytes of multimodal sensor data

* Optimize multimodal data ingestion and preprocessing pipelines (LiDAR, camera, radar, map priors) to support cutting-edge perception and planning model development

* Work across cloud environments to support high-throughput distributed training

* Collaborate closely with the AI research team and autonomy teams

* Technologies:
Pytorch, CUDA, Ray, Flyte, K8s

We're looking for someone who has:

* Experience with building software components to address production, full-stack machine learning challenges.

* Opinions about building a company-wide platform for ML training, evaluation, and deployment

* Knowledge of the open source landscape with judgment on when to choose open source versus build in-house

* Excellent analytical and problem-solving skills

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…