Applied Intuition
AI, Self-Driving Systems, Automotive, Defense, Trucking, Construction, Mining, Agriculture
TechnicalLeadManagerPerception,SelfDrivingSystems
“Technical Lead Manager - Perception, Self-Driving Systems at Applied Intuition. Skills: perception model architecture, perception model training, perception model evaluation, perception model deployment, camera-first perception strategy, model performance across full deployment surface, model lifecycle management, on-vehicle driving outcomes. Own the perception model end-to-end: architecture, training, evaluation, and deployment. Drive a camera-first perception strategy”
What You'll Achieve.
building a model that generalizes across geographies, road types, sensor setups, and environmental conditions without per-vertical forks; progressively reduce dependencies on HD maps and lidar; deliver physical intelligence
Industry & Context.
understanding why perception regresses and fixing it
What They're Looking For.
Must Have
5+ years in ML/deep learning for perception or 3D scene understanding, Deep hands-on experience training and deploying vision models at scale, 2+ years managing or technically leading a perception team, Software engineering in Python and C++, Experience scaling perception models across multiple geographies, sensor setups, or vehicle platforms
Nice to Have
Deep familiarity with transformer-based architectures for 3D perception, BEV representations, Multi-task learning, Dense prediction, Familiarity with occupancy-based scene representations, Sparse query-based architectures, Temporal aggregation approaches, Experience reducing or removing map dependencies in perception systems, Background in autolabel pipelines, Data quality monitoring, Data flywheel design for perception, Experience with closed-loop simulation for perception model evaluation (neural sim, log sim, scenario-based testing), Experience at an AV company that has shipped perception to production
What You'll Do.
Own the perception model end-to-end: architecture
Drive a camera-first perception strategy
Lead training and iteration cycles hands-on
Own model performance across the full deployment surface
Manage the model lifecycle from training through quantization and deployment on embedded compute
Close the gap between what the model does offboard and what it does on the vehicle
Work directly with OEM customer programs to understand sensor configurations
and performance requirements
Translate these into model architecture and data strategy
and technically lead a team of perception engineers
Set high technical standards
How You'll Work.
Team & Collaboration
Work directly with OEM customer programs
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