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# Senior Computer Vision Engineer (Egocentric), Data Foundry

- **Company:** Enduralock, LLC
- **Location:** Atlanta, GA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** 3D Scanning, Artificial Intelligence, Computer Vision, C++ (Programming Language), Python (Programming Language), Data Ingestion
- **Published:** October 3, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pouaj35dk0

## About the Role

* 8+ years building and shipping production computer vision/perception systems, or an MS/PhD in computer vision, ML, or robotics with 6+ years of hands-on industry experience.
 * Experience building and scaling an egocentric perception or video data stack end to end, ideally within robotics, physical AI, or an AI data company.
 * Deep expertise in computer vision, including detection, tracking, segmentation, depth, 2D/3D pose estimation, and vision transformers.
 * Strong command of geometric computer vision, including camera calibration, multi-view geometry, synchronization, and 3D reconstruction.
 * Proven ownership of complex perception problems from data and model design through evaluation, optimization, and deployment, with measurable improvements in accuracy and reliability.
 * Experience working with large, unstructured video and multimodal datasets, with a disciplined approach to evaluation and quality measurement.
 * A track record of setting technical direction and raising the bar for other engineers.
 * Proven ability to take ambiguous 0*1 problems from concept to working system with limited resources and no established playbook.
 * Expert-level Python and strong software engineering fundamentals; C++ experience where performance demands it.
 * Most importantly, you're a builder. You're comfortable moving between hardware, data, models, infrastructure, and operations to make the system work.

## Description

* A structural data advantage. Direct access to real-world warehouse environments, workflows, and human activity at significant scale.
 * A massive and rapidly growing market. Build data products for companies developing the next generation of robotics and physical AI.
 * True 0*1 ownership. Shape the product, technology, team, and operating model from the beginning.
 * Direct partnership with the CTO & Co-Founder. Work closely with company leadership to define the technical and commercial direction of the business.

What You'll Do

You will own the early egocentric video and perception stack-from data collection and camera rigs through vision models, processing pipelines, and dataset delivery. This is a hands-on builder-operator role: you'll define what needs to be built, build the critical pieces yourself, and work with a small team to operationalize and scale them.

You Will

 * Define and build the data product. Own the product across quality tiers-from RGB egocentric video to depth-enhanced and multimodal capture with hand pose, body pose, and annotations. Prioritize what gets built based on customer demand and hold a high bar for data quality.
 * Stand up the capture operation. Own camera and rig selection, hardware setup, enrollment, edge processing, data ingestion, and the pipelines that turn raw capture into production-ready datasets. Partner closely with warehouse operations, engineering, and customers to deliver on spec and on schedule.
 * Build the perception stack. Develop detection, tracking, segmentation, depth/3D reconstruction, 6DoF, and multi-view 3D hand/body pose estimation across egocentric and fixed-camera systems.
 * Automate labeling at scale. Build VLM-assisted and automated labeling workflows with human-in-the-loop QA, reducing the cost of annotation while maintaining rigorous quality standards.
 * Own the hardware-vision intersection. Drive camera calibration, epipolar and multi-view geometry, frame-accurate synchronization, and 3D pose triangulation across multi-camera and egocentric rigs.
 * Train and ship models. Design, fine-tune, optimize, and deploy computer vision and multimodal models against large, unstructured video datasets. Build reproducible systems that perform reliably in production-not models that live in a notebook.