Physical Intelligence

Physical Intelligence is building a platform to bring general-purpose AI into the physical world, powering robots with foundation models and learning algorithms. As an API Product Engineer, you will develop the core product surface that enables external companies to utilize Pi's models similarly to how they use LLM APIs today. This involves allowing them to bring their own data, fine-tune models, evaluate performance, and run low-latency inference within their own environments. You will own this entire experience, transforming close-knit collaborations into a scalable platform designed to support a vast number of robots.

Physical Intelligence is building general-purpose AI for the physical world, developing foundation models and learning algorithms for robots and future physically-actuated devices. The Infrastructure team is central to this mission, building and operating the backbone for training state-of-the-art VLA models, large-scale simulation, and reliable deployment of intelligence across robot fleets. This role involves collaborating closely with researchers, robotics runtime, product, and platform engineers to ensure infrastructure scales from prototype to production-grade deployments.

Physical Intelligence is seeking a Software Engineer focused on AI productivity to build and deploy tools that enhance AI utilization across the company. This role involves close collaboration with various teams, including engineering, research, and operations, to identify opportunities for AI leverage and translate them into robust internal tools and workflows. The position is within the Runtime team, which focuses on core systems for operational and research efficiency, alongside engineers working on build systems, infrastructure, and developer productivity. The primary focus will be on AI tooling, making AI agents, assistants, integrations, and automation valuable across the organization.

Physical Intelligence is building general-purpose AI for the physical world, developing foundation models and learning algorithms for robots and future devices. As an ML Infra Engineer focused on Data Systems, you will construct and manage the data infrastructure essential for large-scale robot learning. Your work will bridge raw data sources and the training/evaluation phases, ensuring speed, accuracy, and reliability as systems scale. This role is a systems-focused position at the intersection of distributed systems, storage, and machine learning infrastructure.

Physical Intelligence is developing foundation models and learning algorithms to power future physically-actuated devices. In this role, you will be instrumental in scaling and optimizing our training systems and core model code. You will take ownership of critical infrastructure for large-scale training, encompassing GPU/TPU compute management, job orchestration, and the creation of efficient, reusable JAX training pipelines. This position offers a hands-on, high-leverage opportunity at the intersection of machine learning, software engineering, and scalable infrastructure, working closely with researchers and model engineers to translate innovative ideas into production-ready training runs.