Building intelligence
for physical machines.
Xolver is building systems that help machines understand changing work, predict what may happen, check actions before movement, run close to the machine, and leave records people can review.
We are looking for people who want to work on world models, safety checks, local operation, Console workflows, and the messy realities of deploying intelligence into machines.
- Physical Intelligence Infrastructure
- Safety Checks Before Movement
- Human-Machine Synergy
Noida is our crucible.
This work happens close to hardware. Our Noida lab is where model behavior, controls, sensors, and real machine constraints meet, which is why many roles require proximity to the systems we are building.
Architecting the future.
These are roles for people who want to work on technical systems that touch hardware, operations, and deployment reality. Explore the current missions.
Head of Growth
Define and own the global go-to-market for intelligent machine workflows. No template exists so you must build it.
Role Brief
Physical AI Engineer (Internship)
Build and evaluate models for tasks such as spatial awareness, object manipulation, and trajectory prediction.
Role Brief
Founding ML & Foundation Model Engineer
Design and train machine-learning systems that help robots perform useful tasks under real-world variation.
Role Brief
Founding Embedded & Safety Systems Engineer
Design and implement the local checks that keep proposed machine behavior inside approved operating envelopes.
Role Brief
Founding Robotics & Autonomy Engineer
Lead physical setup, calibration, and integration of robotic platforms. Ensure actuators, sensors, and software workflows are synchronized.
Role Brief
Member of Founder’s Office
You will own the early-stage recruiting pipeline, sourcing world-class engineering talent on LinkedIn and ensuring every candidate experience reflects Xolver’s first-principles culture. You manage the logistics so the founder can focus on the technical bar.
Role Brief
Strong fit, no exact role.
If your background cuts across physical intelligence, world models, robotics, controls, product design, or industrial deployment and you do not see a clean fit yet, reach out directly.
"People who want to work where models meet hardware, and where technical decisions have physical consequences."