ML Optimization Engineer: Training & Inference

Generalist; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Generalist is seeking an expert in machine learning optimizations to join our innovative team. You will own the optimizations for both training and on-robot inference stacks, focusing on achieving step-function gains. The ideal candidate should be proficient with the latest ML techniques and passionate about advancing robotics.

Our mission is to make general-purpose robots a reality, combining expertise from leading AI and robotics labs to push the boundaries of what robots can achieve. Join us as we build the future of AI-integrated robotics.

Qualifications

• Proficient in the latest ML techniques for optimizations.
• Ability to chase ML optimizations from CUDA to frontend/backend.

Responsibilities

• Owning optimizations on training and inference stacks.
• Implementing changes for step-function gains.
• Optimizing both inference and training processes.

Skills

ML techniques for training and inference optimizations

CUDA kernels

Python

torch

numpy

Job description

Generalist is seeking an expert in machine learning optimizations to join our innovative team. You will own the optimizations for both training and on-robot inference stacks, focusing on achieving step-function gains. The ideal candidate should be proficient with the latest ML techniques and passionate about advancing robotics.

Our mission is to make general-purpose robots a reality, combining expertise from leading AI and robotics labs to push the boundaries of what robots can achieve. Join us as we build the future of AI-integrated robotics.