Senior Research Engineer, Computer Vision

About the role

About Tutor

We believe robots are the biggest lever we have to making the physical world a better, more affordable place. But robots are a rounding error in our society: nearly nine out of ten American factories and warehouses don’t even have a single robot, and robots have yet to make their way into our homes or places of business.

Tutor Intelligence is changing that.

Tutor is a robotics research and deployment company, building generally capable robot hardware and artificial intelligence to enable robots to go where no robots have gone before. Sonny is a semi-humanoid robot with frontier dexterity approaching the human form. Cassie does back-breaking work, moving boxes, pallets, and bulk goods for businesses from family-owned manufacturers to some of the largest brands in the world. Tutor robots are manufactured at scale and operate as a network, combining the whole fleet’s learned experience to train ever more capable robot artificial intelligence.

Founded at MIT and headquartered in Watertown, MA, our team is full stack: we design and manufacture robot hardware, train our own models, work directly with the smallest and largest end-customers, and maintain our fleet across the United States. We’re a team of researchers, engineers, technicians, operators, and sellers who love building things and solving hard problems.

Our mission is grand: robots everywhere, for the common good, raising the standard of living across North America, and then the world.

The Role

Tutor's research team pushes the frontier of robot capability across the full stack. Researchers have access to 100+ robots for data collection and evaluation, a massive network of teleoperators, scaled hardware and manufacturing infrastructure, and the ability to collect real world data at enormous scale. Our work covers the complete lifecycle of real-world data generation and model training from initial behavior cloning to post-training with supervised fine-tuning and reinforcement learning. And researchers and research engineers work closely with applied engineers to develop novel techniques into robot products that can be deployed at scale.

You'll own perception for robot manipulation research, from problem definition and data collection through evaluation and integration on physical robots, combining camera geometry and learned models with decisions grounded in measured performance.

What you'll work on - Define the approach and success criteria for open perception problems in robot manipulation.

- Build and integrate detection, segmentation, tracking, object pose estimation, and 3D scene understanding.

- Own camera calibration, coordinate transforms, synchronization, and checks that catch degraded sensor quality.

- Build reproducible datasets and evaluations that cover changes in objects, lighting, viewpoint, and occlusion.

- Choose between geometric methods and learned models based on accuracy, latency, and robustness on the robot.