🛠 Tech Stack

💼 About This Role

You'll drive ML performance optimization for on-road and off-road ADAS/AD stacks, targeting deployment on embedded compute platforms. Your work will directly impact the efficiency and latency of model inference for real-world autonomous systems. This role offers deep technical challenges across the full ML framework stack.

🎯 What You'll Do

• Drive ML performance optimization on multiple technologies for ADAS/AD stacks
• Develop compute usage strategies to optimize efficiency and latency
• Work on model pruning and quantization for memory constrained platforms
• Profile model performance on target embedded compute platforms

📋 Requirements

• Bachelors in Electrical Engineering or Computer Science
• 3+ years of experience with ML accelerators, GPU, CPU, SoC architecture
• Strong embedded programming skills
• Experience profiling and optimizing model performance on embedded compute platforms

✨ Nice to Have

• M.Sc or PhD in a ML related area
• Built an ML optimization framework from scratch
• Deployed ML solutions to embedded chips for real time robotics

🎁 Benefits & Perks

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

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Onsite Interview· 4 hours