Founding Computer Vision & Robotics Engineer (Visa Sponsorship - United States)

Visa sponsorship available. An early-stage industrial automation startup is hiring its first engineer to build a perception system that understands manual work on factory floors. You will take computer vision work from experimentation to production, starting with real-time quality inspection, and help define the technical foundations for later robotic automation. The role carries real ownership and a voice in how the engineering team and technical direction take shape.

What you'll do

• Build perception systems covering detection, classification, tracking, temporal understanding and 3D vision.
• Develop first-person vision that holds up under camera motion, changing viewpoints, occlusion, motion blur and variable lighting.
• Partner with technical leadership to improve models, datasets and evaluation using lessons from live deployments.
• Build geometric vision capabilities such as calibration, localization, pose estimation and coordinate transforms.
• Train and debug PyTorch models using both synthetic and real-world data, and optimize low-latency inference for NVIDIA Jetson with TensorRT.
• Work on the factory floor and turn deployment experience into reusable perception infrastructure.

What you need

• At least 3 years building and deploying computer vision, robotics perception or applied machine learning systems beyond notebooks or lab settings.
• Experience shipping real-time perception in areas such as computer vision, industrial robotics, AR/VR, ADAS or physical AI.
• Strong Python, PyTorch and OpenCV skills, including detection, classification or tracking models.
• Background in geometric vision and in owning an ambiguous physical-world problem from development through deployment.
• Experience with edge deployment or production inference optimization, ideally working alongside users or in field deployments.
• Nice to have: synthetic data and Sim2Real, SLAM or VIO, depth estimation, 3D reconstruction, CUDA, TensorRT, ROS2, robot manipulation or robot learning.

How to apply

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