Applied
ML Runtime Optimization Engineer
Sunnyvale. Posted 20 months ago
The role
You will drive ML performance optimization on multiple technologies for ADAS and AD stacks. You will develop compute usage strategies and work on model pruning and quantization for embedded compute platforms.
What you will do
- Drive ML performance optimization on multiple technologies for on-road and off-road ADAS / AD stacks
- Develop compute usage strategies to optimize efficiency and latency of model inference
- Work on model pruning and quantization
- Support deployment on memory constrained platforms
- Collaborate with ML engineers and software developers on model architecture solutions
- Set up methodologies to profile model performance on target embedded compute platforms
Required qualifications
- Bachelors in Electrical Engineering or Computer Science, OR B.Sc. in Computer Science, Mathematics, Physics or a related field
- 3+ years of experience with ML accelerators, GPU, CPU, SoC architecture and micro-architecture
- Strong software development skills with the focus on embedded programming
- Experience profiling and optimizing model performance on embedded compute platforms
- Experience in working with deep learning frameworks (e.g. PyTorch, JAX, ONNX, etc.)
Nice to have
- M.Sc or PhD in a ML related area
- Built an ML optimization framework from scratch before
- Deployed ML solutions to embedded chips for real time robotics applications
Benefits
- Base salary
- Equity in the form of options and/or restricted stock units
- Comprehensive health, dental, vision, life and disability insurance coverage
- 401k retirement benefits with employer match
- Learning and wellness stipends
- Paid time off
About the company
Applied Intuition, Inc. is a Silicon Valley company creating digital infrastructure for physical AI. It services the automotive, defense, trucking, construction, mining and agriculture industries.