Software Engineer; SDS Core - Evaluation

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

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

SDS Evaluation owns how Applied Intuition measures the performance of its autonomy stacks. You'll build the datasets, metrics, and visualizations that tell perception, prediction, and planning developers whether a change improved the stack, where it remains weak, and what to work on next — the signal teams use to steer development and that leadership uses to judge release readiness.

This role sits at the intersection of autonomy engineering and measurement. You'll work closely with stack developers to turn their open questions into rigorous metrics, drawing on both real road data and novel synthetic scenario generation to evaluate behaviors too rare or too dangerous to encounter on the road. You'll also improve the evaluation infrastructure itself, making runs fast, reliable, and easy to interpret.

• Define and own metrics for one or more autonomy behavior areas, from requirements through implementation
• Build and curate the datasets — real and synthetic — that those metrics run against
• Design visualizations and reporting that make progressions and regressions obvious at a glance
• Partner with perception, prediction, and planning teams to turn their open questions into measurable signal
• Improve evaluation infrastructure: trigger paths, run time, reliability, and result presentation
• Mentor junior engineers and contribute to defining best practices for data-centric development

• Master’s, PhD, or equivalent work experience in Engineering such as Computer Science, Electrical Engineering, Software Engineering
• 3–5 years of experience in software or data infrastructure engineering
• Expertise in building and scaling data pipelines, distributed systems, or ML infrastructure.
• Proficiency in Python and strong knowledge of data frameworks (Spark, Airflow, Kafka, etc.)
• Experience working with large-scale datasets and understanding data-driven development cycles
• Familiarity with machine learning workflows or model training/deployment, especially automation of those processes
• Strong systems thinking and ability to work across multiple parts of the stack (data, infra, and ML)
• Interest in seeing the direct impact of your infrastructure work on how vehicles perform and improve
• Ability to move fast, learn quickly, and mentor others while growing with the team

• Experience with automotive (AV) or robotics systems
• Experi…