Trace Labs | Remote (USA) | Full Time | https://tracelabs.ai/ Want to join a lean, ambitious, and fast growing startup

Trace Labs is an early-stage startup building data infrastructure for physical AI, specifically focused on transforming real-world human work into structured training datasets for robotics and foundation models. They are hiring experienced engineers (Full Stack, Computer Vision) for a fully remote, lean team with founders who have had a successful exit. The company aims to solve the data bottleneck for embodied AI.

How you'd build it

1. 1Research existing solutions for human-in-the-loop data labeling for robotics and vision tasks (e.g., Scale AI, Labelbox) to understand features and gaps.
2. 2Develop a proof-of-concept web application using Next.js and React to ingest diverse sensor data (images, video, potentially LiDAR) and display it for annotation.
3. 3Implement core annotation tools for object detection, segmentation, keypoint tracking, and event logging within the UI, storing annotations in Neon Postgres.
4. 4Integrate a basic workflow engine to manage annotation tasks and worker assignments, allowing for review and export of structured datasets (e.g., COCO, PASCAL VOC).
5. 5Explore and integrate an open-source or commercial computer vision model for pre-labeling assistance to improve annotation efficiency.
6. 6Design and build data validation and quality control mechanisms into the platform to ensure high-quality training data.

Risks & moats

• Building robust data infrastructure for physical AI requires deep expertise in computer vision, robotics, and large-scale data processing, which goes beyond typical web application development.
• The competitive landscape for data labeling platforms is mature with well-funded incumbents like Scale AI; differentiating requires significant innovation.
• Acquiring and managing a scalable workforce for human-in-the-loop annotation is a significant operational challenge.
• Handling the sheer volume and complexity of real-world sensor data (video, 3D point clouds) for robotics is technically demanding in terms of storage, processing, and visualization.

Original context

Trace Labs | Remote (USA) | Full Time | https://tracelabs.ai/ Want to join a lean, ambitious, and fast growing startup? Trace is building the data infrastructure for physical AI. Robotics and embodied AI are bottlenecked by real-world data. We’re building the platform that turns real-world human work into structured training datasets for robotics and foundation model labs. We’re hiring engineers to help build the core product from end to end. Small, senior team. Fully remote. Experienced founders with a successful exit. Clear communicators. High trust, high bar. Open Roles - Full Stack Engineer: https://jobs.ashbyhq.com/tracelabs/963005ce-f4f1-4d54-957d-1... - Computer Vision Engineer: https://jobs.ashbyhq.com/tracelabs/774fbd47-20ce-4665-9bdb-5... What We Offer - Autonomy, impact, and ownership. As an early employee you’ll shape the product direction and company values. - Competitive salary and significant equity in a fast growing, early stage startup. - Remote employment - work where you want, when you want. - Generous vacation policy - take time whenever you need to recharge. Building a lasting company is a marathon, not a sprint.

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