# Perception Engineer

**Company:** [Applied Intuition](https://hotfix.jobs/companies/applied-intuition)
**Location:** Sunnyvale, CA
**Role:** ML Engineering
**Salary:** $180k – $255k/yr
**Experience:** 5+ years
**Skills:** PyTorch, onnx, TensorRT, Docker, Python, C++, perception systems, ml pipelines, flyte
**Posted:** 2026-07-21

> Perception Engineer owning outcomes for autonomous mining vehicles. Responsible for sensor selection, model adaptation to new sites/domains, diagnosing failures, data strategies, and translating customer needs into technical KPIs and solutions. Requires strong systems understanding of perception/full stack and real-world deployment experience.

## Job Description

## 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.
- Own perception outcomes for autonomous mining vehicles operating across active customer sites.
- Select sensor sets for new vehicles, adapt existing models to new domains and operational design domains.
- Diagnose why a model underperforms on a new site and decide when to fix it yourself versus routing it back to the core team.
- Work at the intersection of perception, planning, controls, and customer requirements, translating mining customer needs into technical approaches and KPIs.
- Collaborate daily with the core autonomy platform team, customer engineering, and BD.
- Help stand up new product lines alongside developing existing ones.

## 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++.

## Nice-to-Haves
- Experience with internal ML pipeline/orchestration tooling (e.g., Flyte).
- Experience with offroad autonomy.

## Compensation
- Base salary range: $180,000 - $255,000 USD annually.
- Total compensation package may also include equity, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off.

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