Software Engineer - Validation Toolset

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 [... source excerpt omitted ...] and their advice to potential candidates. About the role We are looking for a software engineer excited about delivering cutting-edge automotive validation products with a tight customer feedback loop. This role will work across all parts of validation (systems traceability, data ingestion and KPI visualization, coverage analysis, ML-based failure finding). We are looking for someone who can be hands-on in supporting both our external as well as our internal customers across other functions within the company. At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, closely interact with external and internal users to collect feed [... source excerpt omitted ...] sing modern tooling and frameworks Drive the end to end product lifecycle, from the external-facing product to the underlying schemas and infrastructure Build features to enable customers to perform software-driven validation including a unified data layer for systems models, test case orchestration, safety case management, and KPI analysis Enable customers to define and measure coverage of their autonomous systems and dynamically failure-find within the state space using machine learning techniques Design and scale data systems to performantly ingest millions of simulation data points daily and support high-speed querying and visualization through interactive data workflows