Physical Intelligence
AI Frontier · Robotics foundation models (PI)
Hiring velocityscroll left for older weeks
Jobs (7)
| Title | Stage | AI score |
|---|---|---|
| Research Scientist Research Scientist role focusing on machine learning and robotics, requiring a strong record of research results, system-building, and fundamental advances. Open to candidates at all levels with excellent fundamentals and implementation skills. | Data | 10 |
| Robotics Research Engineer Physical Intelligence is seeking a Robotics Research Engineer to develop foundation models and learning algorithms for robots. This role involves working across hardware, software, and large-scale model training, from data collection to policy development and deployment. The engineer will create new data collection methods, develop vision-language-action models, curate datasets, and run experiments to improve policy performance. | DataPost-train | 9 |
| ML Infra Engineer (Supercomputing) ML Infra Engineer responsible for designing and building a scheduling and compute layer for large-scale AI model training across heterogeneous GPU/TPU clusters. This role focuses on intelligent resource allocation, utilization, fault tolerance, and making distributed training seamless, extending to inference and robot deployment. | ServeAgent | 8 |
| Robot Operator This role involves teleoperating robotic arms to collect high-quality demonstration data for training foundation models for physical world AI. The operator will perform various tasks, maintain data quality, and meet collection metrics. It's a hands-on, metrics-driven position focused on generating training data for AI-powered robots. | Data | 8 |
| ML Infra Engineer (TPU/Jax/Optimization) ML Infra Engineer focused on scaling and optimizing training systems and core model code, managing GPU/TPU compute, job orchestration, and building efficient JAX training pipelines. Collaborates with researchers to translate ideas into production training runs. | Data | 8 |
| ML Infra Engineer ML Infra Engineer to scale and optimize training systems and core model code, managing GPU/TPU compute, job orchestration, and JAX training pipelines. Collaborates with researchers to translate ideas into production training runs. | Data | 8 |
| Controls Engineer Controls Engineer for Physical Intelligence, designing and implementing algorithms for robot control, including PID, LQR, MPC, and neural-network-driven control. Responsibilities include building and validating models, developing real-time loops, owning robotic bring-up, debugging complex systems, and working with sensor/actuator subsystems. Requires strong understanding of model-based control, Python/C++ proficiency, and real-time loop tuning skills. Bonus for robot learning or manipulation experience. | ShipServe | 7 |