8+ years experience in autonomous vehicle systems development, perception engineering, motion planning, or AI/ML for L4-5 autonomous systems
Deep familiarity with autonomous vehicle sensor modalities (camera, LiDAR, radar) and their data characteristics including the long-tail distribution and edge case challenges central to L4-5 development
Hands-on ML capability: able to build, validate, and deploy ML solutions independently in Python using modern ML frameworks
Proficient in working directly in JupyterHub, VS Code, Marimo, and W&B Models to build and deploy customer-facing applications
Working knowledge of ML approaches relevant to autonomous systems: perception, object detection, motion prediction, closed-loop simulation, or anomaly detection in autonomous system logs
Able to validate ML solutions on engineering grounds and identify when a result is inconsistent with the physical or safety constraints of the domain
Proven experience leading complex technical customer engagements, managing multi-stakeholder environments, and maintaining executive relationships
Strong understanding of the autonomous vehicle development pipeline, including closed-loop simulation, scenario-based testing, and data driven approaches to safety case validation
Able to translate field observations into structured product signals that are actionable for an engineering team
Bachelor’s or Master’s degree in Electrical Engineering, Systems Engineering, Computer Science, Physics, or a related technical discipline
Knowledge of functional safety standards including ISO 26262 and SOTIF
Experience with simulation environments used in autonomous vehicle development (CARLA, LGSVL or similar)
Familiarity with edge deployment of ML models in constrained or safety-critical environments
Experience identifying and progressing expansion opportunities within strategic customer accounts
Track record of contributing to internal knowledge frameworks, technical publications, or industry forums in the autonomous vehicles space
Experience working alongside or within an AI infrastructure or MLOps environment
Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams — even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk
You are equally comfortable discussing perception algorithm design and long-tail edge case coverage with ML engineers as you are discussing system safety architecture with systems engineers and you know that the most valuable insight often sits at that boundary
You want to build AI solutions that are deployed in real engineering environments, not demonstrated in notebooks
You find the unsolved problem of building autonomous systems that reliably handle the long-tail of real word edge cases to be a genuinely interesting technical problem
You want to bring your autonomous vehicle domain expertise into a team that already knows how to land and expand AI solutions with engineering customers, and you see being the domain authority that opens a new vertical as a genuinely compelling opportunity