Location: New York / New Jersey
Office: Customer floor
Type: Full-time, founding role
Compensation: Base +
equityTravel:Significant, travel-heavyWalk into any busy distribution center and you'll see the problem we're solving. Thousands of products, packaging that changes every season, light that shifts every time a dock door opens. Most picking and case handling is still done by hand, because robots haven't been able to make sense of a scene like that and act on it reliably.
We're hiring the engineer who will lead how our robots see and learn. You'll own perception and robot learning for VisionOS, make the core technical calls, and take our models from simulation onto real robots on
customer floors.
About the RoleThis is a
founding role, and you'll build this part of the product from the ground up with the founding team. There isn't a large existing codebase waiting for you. The perception team recently lost a member, and we need someone who wants to build the next version from scratch, set the technical approach, and operate with a high degree of independence.
Your work runs through the full model lifecycle: perception pipelines, VLA models, pre-training, fine-tuning, deployment, and post-training optimization all the way to inference. For us,
a model is done when it works on the floor, not when the eval curve looks good.
What You'll Own- Perception: 3D scene understanding (RGB-D fusion, point clouds, segmentation), 6-DOF pose estimation for products and cases, and zero-shot identification with vision-language models.
- VLA models: Vision-language-action models as the backbone of how our robots carry out tasks, including pre-training, fine-tuning, and synthetic data in simulation.
- Deployment: Models running on real robots within tight latency and compute limits, plus an active learning loop that turns floor mistakes into better models.
- Data and teleoperation: Teleoperation setup, data collection, and the pipeline from raw recordings to clean, versioned training data.
Your First MonthGet to know our robots, simulation environment, and customer floors, then write the perception and learning plan you want to bet on. By the end of the month, you'll have a
first model running on a physical robot doing a real task.
What You Bring- 3 to 5 years of hands-on work in robotics, computer vision, or ML, ideally on physical robots
- Hands-on model training on GPUs and experience shipping models to production inference under latency constraints
- 3D perception experience with point clouds and depth cameras
- Experience deploying on real robot hardware and working in simulation (MuJoCo, Isaac Sim, or similar)
- Strong Python and C++ (or a similar systems language)
- A habit of getting physical prototypes working in weeks, not months
Nice to Have- VLA or manipulation policy training
- Zero-shot pose estimation or segmentation
- Grasp planning, learned or geometric
- Warehouse or logistics automation experience
TravelThis role is
travel-heavy. Our customer warehouses are our lab, so expect to spend a significant amount of your time on site, deploying and improving systems on live floors. If you need to be home most weeks, this probably isn't the right fit, and we'd rather say so now.
