Perception Team Lead

Description

Join the future of mobility. Help build the platform that's changing how cities move.

NoTraffic is the world’s leading mobility platform, transforming intersections into connected infrastructure that improves flow, boosts safety, and prepares cities for the autonomous era.

We're looking for a technically sharp, people-first leader to head our Perception team. You'll own a domain that sits at the heart of what we do - turning raw sensor data into a variety of traffic-related applications - real-time optimization, safety applications, analytics, and more.

This is a hands-on leadership role: you'll be part of roadmap establishment and in charge of its execution, raise the bar on algorithmic craft, and stay hands-on enough to lead from the front.

Your day to day will look like:

• Own the execution of the algorithmic roadmap in close collaboration with Product, QA, Optics, Infrastructure, Traffic Optimization, and Cloud teams - translating it into executable plans and keeping cross-team dependencies in check.
• Set and enforce engineering standards: code reviews, best practices, and staying current with the field (including AI integration into team workflows).
• Drive execution planning - scope algorithmic work into well-defined stories, set realistic timelines, and protect the team's focus.
• Stay ~20% hands-on in the codebase to remain technically grounded and unblock the team when it matters.

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Requirements

• 3+ years of algorithms management experience, with a track record of leading deep learning teams.
• 5+ years of hands-on algorithm development - you've written production-quality code and can engage deeply on technical tradeoffs, not just manage them from a distance.
• Computer vision and/or radar perception experience - as a practitioner or manager. Radar experience is a significant plus.
• B.Sc. in Computer Science, Electrical Engineering, or a related field (or equivalent practical depth).
• Holistic system and product understanding - you see beyond your team's scope and grasp how perception fits into the broader product and architecture.