Software Engineer: ML Optimization

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

About the Role

We internally call this team MBMB (More Big More Better). You will own optimizations on both the training and on-robot inference stacks. We are still in a regime of step-function, not incremental, gains.

You’ll be responsible for:

• Making GPUs go brrrrr
• Implementing ML, hardware, and software changes that lead to step-function gains
• Optimizing both the inference and training stacks

You might thrive in this role if you:

• Are proficient and stay current with the latest ML techniques for training and inference optimizations in transformer and diffusion based architectures
• Will chase ML optimizations anywhere: From the CUDA kernels, to ML architecture, to frontend or backend network bottlenecks, CPU bottlenecks, NVLink and comms, to torch, numpy, and Python inefficiencies.

About Generalist

At Generalist, we are on a mission to make general-purpose robots a reality. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.

We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.

The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision‑language‑action models (PaLM‑E, RT‑2, Gemini Robotics), launched and scaled ChatGPT and GPT‑4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next‑generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.