ML Runtime Optimization Engineer
Applied Intuition
12 months ago
Mountain View, CA, USA
Mid Level / Senior
H1B Sponsor
Base Salary
$159k - $199k/yr
Responsibilities
- Drive ML performance optimization for ADAS/AD stacks on embedded platforms.
- Provide technical leadership to the ML model performance optimization team.
- Develop strategies to optimize efficiency and latency of model inference.
- Work on model pruning and quantization for memory-constrained platforms.
- Collaborate with ML engineers and software developers on model architecture solutions.
- Profile model performance on embedded platforms and identify bottlenecks.
Requirements
- Bachelor's degree in Electrical Engineering, 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 focused on embedded programming.
- Experience profiling and optimizing model performance on embedded platforms.
- Familiarity with deep learning frameworks such as PyTorch, JAX, and ONNX.
Benefits
- Comprehensive health, dental, vision, life, and disability insurance coverage.
- 401k retirement benefits with employer match.
- Learning and wellness stipends.
- Paid time off.
Tech Stack
PyTorch
Categories
AI & MLEmbedded