Perception Engineer - Offroad

Applied Intuition Applied Intuition · Robotics · Sunnyvale, CA · Self-Driving Systems

Perception Engineer role focused on adapting and deploying AI models for autonomous mining vehicles in real-world customer sites. Responsibilities include selecting sensor sets, adapting models to new domains, diagnosing performance issues, and making build-vs-reuse tradeoffs for new product lines. The role requires a strong systems-level understanding of perception and a product-owner mindset, prioritizing customer success and problem ownership over cutting-edge research.

What you'd actually do

  1. Design and implement perception systems to enable new product capabilities, leveraging existing model heads and solving new perception tasks.
  2. Design the data strategy for a new deployment: what to collect, how much, and how to label it, to get a model production-ready
  3. Make build-vs-reuse tradeoffs when standing up new product lines, including output types, KPIs, and collaboration points with the core perception team
  4. 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

Skills

Required

  • PyTorch
  • ONNX
  • TensorRT
  • Docker
  • Python
  • C++
  • systems-level understanding of perception
  • planning
  • controls
  • diagnosing real-world model failures
  • ambiguous, evolving requirements
  • technical specs

Nice to have

  • internal ML pipeline/orchestration tooling
  • Flyte
  • offroad autonomy

What the JD emphasized

  • diagnosing real-world model failures in deployed systems and driving them to resolution

Other signals

  • adapting existing models to new domains
  • diagnosing why a model underperforms
  • making build-vs-reuse tradeoffs
  • triage model and system issues in the field