About this opportunity
Physical Intelligence lists this Machine Learning Infrastructure Engineer (Modeling) opportunity in san francisco, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
The ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. The team works closely with research, data, and platform engineers to ensure models can scale from prototype to production-grade training runs
Own training/inference infrastructure: Design, implement, and maintain systems for large-scale model training, including scheduling, job management, checkpointing, and metrics/logging
Scale distributed training: Work with researchers to scale JAX-based training across TPU and GPU clusters with minimal friction
Optimize performance: Profile and improve memory usage, device utilization, throughput, and distributed synchronization
Enable rapid iteration: Build abstractions for launching, monitoring, debugging, and reproducing experiments
Partner with researchers: Translate research needs into infra capabilities and guide best practices for training at scale
Contribute to core training code: Evolve JAX model and training code to support new architectures, modalities, and evaluation metrics
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.