Technical Lead Manager - Perception, Self-Driving Systems
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 job
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
Python, C++, Machine Learning, Deep Learning, Computer Vision, 3D Scene Understanding, Transformers, Bev, Multi-Task Learning, Embedded Systems, Model Deployment, Perception Models, Autonomous Vehicles
Similar jobs
ML Engineering jobs
Baselayer
San Francisco, CA
Senior AI Engineer responsible for production LLM agents that enrich business identity data through web discovery, verification, classification, and risk scoring. The role requires strong asynchronous Python, agent and evaluation expertise, browser automation, and experience operating AI systems in production.
Otter
Mountain View, CA
Leads the development and production deployment of large-scale ASR and TTS systems for conversational intelligence products. The role requires 5+ years of industry experience, deep speech-model expertise, and strong software engineering and ML operations capabilities.
Ambience Healthcare
San Francisco, CA
Build and improve production AI systems for clinical products, owning evaluations, model behavior, agentic workflows, data flywheels, deployment, and observability. The role requires 5+ years of production ML or applied AI experience, strong Python and modern ML framework skills, and hands-on debugging expertise.
Dialpad
United States
Leads development of speech models, decoders, and low-latency inference systems for next-generation voice agents. Requires 5+ years in speech ML or related audio AI, strong Python and PyTorch experience, and the ability to guide technical direction and mentor engineers.
Ontario, Canada
Design, build, and deploy production ML systems for recommendations, search, ranking, and advertising at internet scale. Own the full ML lifecycle from modeling to monitoring with strong cross-functional collaboration.