Software Engineer: ML Optimization

Generalist • Somerville, MA

1d • $260,000 - $350,000

About The Position

Generalist is building general intelligence for the physical world, with a focus on embodied foundation models and dexterity. The ML Optimization team, internally called MBMB (More Big More Better), works on optimization across the model-training and on-robot inference stacks. The role focuses on achieving step-function rather than incremental gains through ML, hardware, and software changes.

Requirements

• Proficiency with current ML techniques for training and inference optimization in transformer- and diffusion-based architectures.
• Willingness to pursue ML optimization opportunities across kernels, model architecture, networking, CPUs, communications, and software frameworks and languages.

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