Embedded ML Runtime Optimization Engineer

Applied Intuition; Sunnyvale (CA); Hybrid; USD 159,000 - 199,000; Full time

Job summary

Applied Intuition in Sunnyvale, CA is seeking a software engineer specializing in optimizing ML models for production-grade embedded runtime environments. You will influence the entire ML framework stack across PyTorch, JAX, ONNX, TensorRT, CUDA, XLA and Triton.

You will collaborate with ML engineers and software teams to implement model pruning, quantization, and deployment strategies on memory-constrained embedded compute platforms, delivering efficient, low latency inference.

Qualifications

• Bachelor's degree in Electrical Engineering or Computer Science
• 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.)

Responsibilities

• Drive ML performance optimization on multiple technologies for on-road and off-road ADAS / AD stacks targeting deployment on a variety of embedded compute platforms
• Develop compute usage strategies to optimize efficiency and latency of model inference for compute boards selected by our customers
• Work on model pruning and quantization, and support deployment on memory constrained platforms
• Collaborate closely with ML engineers and software developers on technical efforts to find and optimize efficient model architecture solutions
• Set up methodologies to profile the model performance on target embedded compute platforms and identify performance bottlenecks as part of stack integration

Skills

Embedded programming

ML optimization

Model performance profiling

Education

Bachelor's degree in Electrical Engineering or Computer Science

B.Sc. in Computer Science, Mathematics, Physics or related field

Tools

PyTorch

JAX

ONNX

CUDA

TensorRT

XLA

Triton

Job description

Applied Intuition in Sunnyvale, CA is seeking a software engineer specializing in optimizing ML models for production-grade embedded runtime environments. You will influence the entire ML framework stack across PyTorch, JAX, ONNX, TensorRT, CUDA, XLA and Triton.

You will collaborate with ML engineers and software teams to implement model pruning, quantization, and deployment strategies on memory-constrained embedded compute platforms, delivering efficient, low latency inference.