Senior Computer Vision Engineer

About the Role:

We’re partnering with a fast-scaling startup in SF that is fundamentally changing how physical materials are tracked and measured using real-time 3D computer vision.

If you're passionate about bringing SOTA 3D vision algorithms out of the research lab and into high-impact, real-world industrial environments, this role gives you full ownership over the core perception engine.

They are looking for an experienced Senior Computer Vision / Perception ML Engineer to own the perception engine that converts raw stereo camera captures into accurate, production-grade 3D measurements for industrial applications.

This role sits directly at the core of our tech stack. You will be responsible for taking complex research pipelines—covering stereo reconstruction, point-cloud cleanup, depth estimation, and 3D volumetric metrics—and turning them into robust, production-ready algorithms.

What You Will Own

• The core end-to-end CV/ML pipeline: stereo reconstruction, point-cloud processing, segmentation, ground-plane estimation, stitching, and volume calculation.
• Model integration using SOTA architectures (FoundationStereo, YOLO-style models, s2m2).
• System calibration, confidence metrics, failure-mode analysis, and 3D reconstruction quality.
• Bridging the gap between prototype research and deployable, real-world sensor performance.

What We’re Looking For

• Experience: 4+ years of hands-on experience in computer vision, robotics perception, or ML engineering.
• 3D Vision Focus: Deep expertise in 3D geometry, camera calibration, stereo/depth estimation, point clouds, and segmentation.
• Core Tech Stack: Proficient in Python, PyTorch, OpenCV, and Open3D.
• Real-World Engineering: Proven track record of debugging noisy sensor data and shipping CV systems in real-world environments.
• Education: MS or PhD in Computer Vision, Robotics, or a related field preferred.

Nice-to-Haves

• Hands-on experience with CUDA, SLAM, photogrammetry, or geospatial/volumetric measurement.
• Experience with cloud GPU infrastructure (e.g., Modal).
• Prior perception experience in robotics, autonomous vehicles, or industrial inspection.