Software Engineer: ML Optimization
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At a glance
Job overview
Generalist is hiring a Software Engineer: ML Optimization. The role is part of Generalist’s MBMB team, focusing on step‑function improvements to both training and on‑robot inference stacks for embodied foundation models, leveraging advanced ML techniques and hardware optimizations.
Key focus areas include Make GPUs go brrrrr, Implement ML, hardware, and software changes that lead to step‑function gains, and Optimize both the inference and training stacks.
Preferred (not required): ML Techniques For Training And Inference Optimizations, Transformer Based Architectures, Diffusion Based Architectures, and CUDA Kernels.
Skills & qualifications
Skills
Full 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:
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Making GPUs go brrrrr
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Implementing ML, hardware, and software changes that lead to step-function gains
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Optimizing both the inference and training stacks
You might thrive in this role if you:
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Are proficient and stay current with the latest ML techniques for training and inference optimizations in transformer and diffusion based architectures
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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.
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