A

Applied Intuition

Builds software for autonomous vehicles

ML Runtime Optimization Engineer

Applied Machine LearningUpdated on Nov 11
Full-timeSunnyvale, CA, USA$215k - $315k /yr

About the Job

Requirements

  • A bachelor's degree in Electrical Engineering or Computer Science, or a Bachelor of Science in Computer Science, Mathematics, Physics, or a related field.
  • At least 3 years of experience with machine learning accelerators, GPUs, CPUs, system-on-chip architecture, and microarchitecture.
  • Strong software development skills focused on embedded programming.
  • Experience profiling and optimizing model performance on embedded compute platforms.
  • Experience working with deep learning frameworks such as PyTorch, JAX, or ONNX.

Responsibilities

  • Drive machine learning performance optimization across multiple technologies for on-road and off-road advanced driver-assistance system and autonomous driving stacks targeting deployment on various embedded compute platforms.
  • Develop compute usage strategies to optimize model-inference efficiency and latency for compute boards selected by customers.
  • Work on model pruning and quantization, and support deployment on memory-constrained platforms.
  • Collaborate closely with machine learning engineers and software developers on technical efforts to find and optimize efficient model architecture solutions.
  • Set up methodologies to profile model performance on target embedded compute platforms and identify performance bottlenecks as part of stack integration.

Desired Qualifications

  • A Master of Science or PhD in a machine-learning-related area.
  • Experience building a machine-learning optimization framework from scratch.
  • Experience deploying machine-learning solutions to embedded chips for real-time robotics applications.

About the Company

Applied Intuition

Builds software for autonomous vehicles

Applied Intuition builds software for automakers and operators developing autonomous vehicles and other machines, from passenger cars to industrial equipment. Its Tools for Vehicle Intelligence let engineers test driving behavior in simulated worlds, while Vehicle OS connects software inside a machine with development tools off the vehicle. The Self-Driving System supports driver assistance and fully driverless operation for passenger and commercial vehicles. It sells these systems to businesses and works alongside their engineers to integrate, validate and update vehicle software. Applied Intuition was founded in 2017 and is headquartered in Sunnyvale, California.

Company size
1,001-5,000
Company stage
Series F
Total funding
$1.2B
Headquarters
Sunnyvale, CA
Founded
2017

Recently Posted Jobs

Explore more opportunities at Applied Intuition

See more jobs