- Robot type
- Autonomous Vehicle · Robot AI and Software
- Location
- SunnyvaleCaliforniaUSA
- Job type
- Artificial Intelligence
- Posted
- Jul 21, 2026
- Salary
- $180,000–$255,000 a year
Perception Engineer - Offroad
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.;
Job responsibilities
- Design and implement perception systems to enable new product capabilities, leveraging existing model heads and solving new perception tasks.
- Design the data strategy for a new deployment: what to collect, how much, and how to label it, to get a model production-ready
- Make build-vs-reuse tradeoffs when standing up new product lines, including output types, KPIs, and collaboration points with the core perception team
- Triage model and system issues in the field — timestamps, data quality, calibration, and similar — and decide whether to resolve them directly or work with the core platform team to fix them upstream
Job requirements
- Strong systems-level understanding of perception (and ideally planning/controls) — enough to reason about the full stack, even without owning model training personally
- A product-owner mindset: motivated by customer success and problem ownership more than by being on the cutting edge of modeling research
- Experience diagnosing real-world model failures in deployed systems and driving them to resolution, whether hands-on or through cross-team negotiation
- Comfort working with ambiguous, evolving requirements from customers and translating them into technical specs
- Familiarity with PyTorch, ONNX, TensorRT, Docker, Python, some C++
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