🛠 Tech Stack

💼 About This Role

You'll lead the team that trains, evaluates, and ships the core perception model for autonomous vehicles across multiple geographies and sensor configurations. You'll own model performance end-to-end, driving camera-first perception strategy and reducing dependencies on HD maps and lidar. This role offers the chance to shape the autonomy stack deployed on real vehicles worldwide.

🎯 What You'll Do

• Own perception model end-to-end: architecture, training, evaluation, deployment
• Drive camera-first perception strategy and reduce dependency on HD maps and lidar
• Lead training and iteration cycles hands-on, analyzing data and evaluations
• Manage model lifecycle from training through quantization and embedded deployment

📋 Requirements

• 5+ years in ML/deep learning for perception or 3D scene understanding
• Hands-on experience training and deploying vision models at scale
• 2+ years managing or technically leading a perception team
• Experience deploying perception models to embedded hardware under real-time constraints

✨ Nice to Have

• Deep familiarity with transformer-based architectures for 3D perception
• Experience with occupancy-based scene representations or temporal aggregation
• Background in autolabel pipelines or data flywheel design for perception

🎁 Benefits & Perks

• 💰 Equity in the form of options and/or restricted stock units
• 🏥 Comprehensive health, dental, vision, life and disability insurance
• 📈 401k retirement benefits with employer match
• 🎓 Learning and wellness stipends
• 🏖️ Paid time off

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min
4. 4Onsite (4-5 rounds)· 4 hours