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Technical Lead Manager - Perception, Self-Driving Systems

232k – 298kSunnyvale, CAOnsite5+ YOE
Summary

Leads team developing and deploying a unified camera-first perception model for self-driving systems across diverse vehicles, geographies, and conditions. Hands-on with ML architecture, training, evaluation, embedded optimization, and customer requirements. Requires 5+ years ML perception experience and 2+ years team leadership.

About the role

Responsibilities

  • Own the perception model end-to-end: architecture, training, evaluation, and deployment across geographies, road types, sensor setups, and environmental conditions.
  • Drive a camera-first perception strategy to reduce dependencies on HD maps and lidar.
  • Lead training and iteration cycles hands-on, including data analysis, eval dashboards, and failure analysis.
  • Own model performance across full deployment surface: highway, urban, residential, ramps, complex intersections, poor weather, hilly terrain.
  • Manage model lifecycle from training through quantization and deployment on embedded compute with device-specific optimizations.
  • Work directly with OEM customer programs to understand sensor configurations, target ODDs, and performance requirements.
  • Recruit, develop, and technically lead a team of perception engineers.

Requirements

  • 5+ years in ML/deep learning for perception or 3D scene understanding with hands-on experience training and deploying vision models at scale.
  • 2+ years managing or technically leading a perception team.
  • Experience building production perception systems, especially camera-only or camera-first solutions.
  • Track record deploying perception models to embedded hardware under real-time latency and compute constraints.
  • Strong software engineering in Python and C++ across the stack from training to onboard inference.
  • Experience scaling perception models across multiple geographies, sensor setups, or vehicle platforms.

Nice to Haves

  • Deep familiarity with transformer-based architectures for 3D perception, BEV representations, multi-task learning, and dense prediction.
  • Familiarity with occupancy-based scene representations, sparse query-based architectures, or temporal aggregation approaches.
  • Experience reducing or removing map dependencies in perception systems.
  • Background in autolabel pipelines, data quality monitoring, or data flywheel design for perception.
  • Experience with closed-loop simulation for perception model evaluation.
  • Experience at an AV company that has shipped perception to production.

Compensation

Base salary range: $231,900 - $298,100 USD annually, plus equity and benefits.

Skills
PythonC++Machine LearningDeep LearningComputer Vision3D Scene UnderstandingTransformersBEVMulti-task LearningEmbedded SystemsModel DeploymentPerception ModelsAutonomous Vehicles
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