Systems Engineer, Insights and Analytics (SDS Trucking) at Applied Intuition in Sunnyvale

  • Company: Applied Intuition
  • Location: Sunnyvale
  • Job type: full time
  • Workplace: onsite
  • Posted: 2026-10-28

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Job description

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 We are looking for a Systems Engineer with a strong data background to own insights, analytics, and development metrics for our SDS trucking team. You’ll analyze driving data to help the self-driving trucking team understand system performance, identify areas for improvement, and make informed engineering decisions. You will combine hands-on data analysis, statistical reasoning, and systems engineering to turn complex data into insights that shape development, support verification and validation (V&V), and inform launch readiness. At Applied Intuition, you will: • Define development and autonomy performance metrics, and implement them in code against fleet, test, and simulation data • Build data pipelines, analyses, and tools using Python, SQL, or similar technologies to turn large datasets into insights on performance, gaps, and launch readiness. • Track metrics over time, catch regressions early, and guide engineering priorities with data • Read autonomy stack code to trace system behavior back to requirements and root causes • Work with systems engineers to translate requirements into measurable metrics and evaluation criteria. • Drive verification and validation across simulation, closed-course, and on-road testing • Build dashboards and readiness views for engineering leadership and customers • Collaborate across autonomy, perception, hardware, safety, and test teams We're looking for someone who has: • 3+ years of experience in data science, data engineering, systems engineering, V&V, or a related role in ADAS, autonomous driving (L2–L4, L4 preferred), or robotics. • MS/BS in Systems, Electrical, Mechanical, Computer Science, Robotics, Data Science, or equivalent • Hands-on experience analyzing large datasets with Python and SQL, including statistical analysis, data visualization, and interpreting variability and uncertainty. • Experience defining and reporting metrics that drive decisions on a development program • Ability to read production code (Python, C++, or similar) well enough to trace behavior through an autonomy or robotics stack • Strong systems engineering fundamentals: requirements, functional decomposition, architecture, and test planning • Experience with V&V for ADAS/AD or robotics, including defining what is sufficient for launch • Working knowledge of fault management and a solid understanding of AV stack components • Strong communication skills for explaining data-driven findings to engineers, leadership, and customers Nice to have: • Autonomous trucking, off-highway, or off-road autonomy experience. • Simulation-based validation and scenario-based testing D

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