Staff Research Engineer, Robot Learning Systems

Location: Milpitas, CA; requires 5 days/week in-office collaboration

Salary: $225,000–$265,000 USD + bonus + equity

Company

hirify.global is an AI robotics company developing Physical AI-powered robots for dull, dirty, and dangerous industrial work, with a focus on real-world deployment and scalability.

What you will do

• Lead engineering for the embodied systems powering the data flywheel: onboard AI inference, data collection, teleoperation, and on-robot reinforcement learning.
• Set the technical direction and architecture for running, evaluating, and improving learned models on real robots.
• Deliver systems end-to-end on physical robots, from bring-up through reliable real-time operation in demanding industrial environments.
• Own on-robot deployment and closed-loop policy evaluation, converting real-world performance into measurable improvements.
• Align interfaces and priorities with the robotics software and ML research teams.
• Mentor engineers and raise the technical bar for embodied systems work.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, or a related field with significant relevant experience, or a PhD.
• Track record of leading complex robotic or embodied systems end-to-end and setting technical direction for other engineers.
• Strong proficiency in both C++ and Python, with solid systems programming and real-time or performance-critical engineering skills.
• Hands-on experience with ROS or ROS2 and robot middleware, including real-time integration of sensing, control, and compute.
• Experience integrating and deploying ML models or policies into real-time robotic or autonomous systems, with emphasis on system ownership and building rather than model training or research.
• Must collaborate in the office 5 days per week.

Nice to have

• Experience with teleoperation and data-collection systems such as VR, UR, GELLO, or UMI, including collecting high-quality robot data at scale.
• Experience with on-robot reinforcement learning or closed-loop policy-improvement systems.
• Familiarity with robot learning policies such as VLA, imitation learning, or behavior cloning, including real-time inference and control integration.
• Familiarity with manipulation stacks, whole-body control interfaces, or real-time middleware tuning.

Culture & Benefits

• Full-time U.S. position with competitive stock options or equity programs.
• Health, dental, and vision insurance and a 401(k) plan.
• Visa sponsorship and green card support for qualified candidates.
• Lunches and dinners, a fully stocked kitchen, and regular team-building events.