Physical Intelligence에서 로봇 배포 및 정책 최적화를 담당할 Applied Researcher를 채용합니다. 실제 환경에서의 로봇 배포 경험과 Python 기반의 강력한 엔지니어링 역량이 필수입니다. 연구와 운영의 가교 역할을 수행하며, 실제 현장에서 로봇의 성능을 개선하고 문제를 해결하는 데 집중합니다. 로봇 공학 및 AI 분야의 실무적 문제 해결에 열정적인 분을 찾습니다.
Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.
The Deployments team is responsible for solving real world problems with our models and robots. We tackle the full problem space: integrating with customer workflows, training models to solve their dexterous tasks, and ensuring the on-site reliability of the system. This breadth of problem space is why we’re a full-stack robotics team - whether it’s thinking about customer facing experiences or fine-tuning models for tasks no robot has done before, we put forth the best solution Pi has to offer.
Deploy and debug learned policies on physical robots, diagnosing failures across the full stack (perception, policy, control, hardware).
Train and tune policies, curate data, and iterate to improve real-world performance.
Write production-quality code that interfaces with Pi’s infrastructure.
Work with operators to set up tests, evals, and data collection pipelines.
Engage with partners to understand use cases and observe robots in deployment contexts.
Bridge research and operations: translate research advances into deployable systems, and surface real-world failure modes back to researchers and (software and hardware!) engineers.
Define and shape a vision for what real-world deployments will look like in the long-term
Hands-on experience deploying robots or autonomous systems in real-world environments
Strong engineering skills: clean Python, ability to interface with infrastructure, debugging instincts
Ability to debug the full stack from perception to control
Practical mindset: motivated by making things work, not by open-ended research
Clear communication with researchers, operators, and occasionally partners
Founded or worked at an early-stage robotics or AV company
PhD in relevant field
Intuition for policy training, neural network debugging, and data curation
Experience with robot manipulation platforms
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
