Software Engineer: ML Optimization

Generalist • Somerville, MA

1d

About The Position

Generalist builds embodied foundation models for the physical world, beginning with a focus on dexterity. The company works across data, models, and hardware, combining large-scale AI and robotics. Its team includes researchers, roboticists, and company builders with experience at frontier technology organizations.

The Software Engineer: ML Optimization will join the team internally called MBMB (More Big More Better) and own optimizations across both training and on-robot inference stacks. The work focuses on achieving step-function rather than incremental gains through changes spanning machine learning, hardware, and software.

Requirements

• Proficiency with the latest machine-learning techniques for training and inference optimization in transformer- and diffusion-based architectures.
• Willingness to pursue ML optimizations across the stack, including CUDA kernels, ML architecture, network and CPU bottlenecks, NVLink and communications, and torch, numpy, and Python.

Responsibilities

• Own optimizations on the training and on-robot inference stacks.
• Implement ML, hardware, and software changes that lead to step-function gains.
• Optimize both inference and training stacks.
• Pursue optimization opportunities across CUDA kernels, ML architecture, frontend and backend network bottlenecks, CPU bottlenecks, NVLink and communications, and inefficiencies in torch, numpy, and Python.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed