About the RoleFrontier AI is going physical, and the labs building it are bottlenecked on one thing: high-quality data from the real world. Mercor pairs its operational scale with the specialized engineering that physical-world data demands.
You'll build the data backbone of physical AI: the pipelines that take raw multi-sensor capture from the field (video, depth, inertial, audio, and more) and turn it into validated, privacy-safe, delivery-ready datasets for frontier labs. Ingest, segmentation, pre-labeling, automated QC, and packaging, at petabyte scale across thousands of concurrent collectors.
What You'll Do- Build the end-to-end sensor data pipeline: ingest from capture devices in the field, through segmentation, pre-labeling, QC, and packaged delivery to customers
- Design automated QC that validates recordings at scale: timing and sync integrity, calibration health, sensor continuity, coverage against requirements
- Establish dataset schemas, versioning, provenance, and versioning, so every delivery has a clear system traceability
- Build shared processing components such as privacy redaction, transcription, encoding, format packaging across all offerings
- Integrate VLM-assisted pre-labeling and quality scoring into production workflows without sacrificing debuggability or human oversight
What Makes This Role Different- High ownership, early. This is a young, strategically central product area; the product you build will shape Mercor's physical-world data collection standards
- The data is the deliverable. The end product at Mercor is the data; what your pipeline produces is what shapes the models that large frontier lab trains on
- Real physical-world scale. Your inputs come from devices operated by humans in global real world settings, for thousands of hours. Building systems that scale is precedent.
What We're Looking For- Strong production backend/data engineering experience - you've built and owned high-volume data pipelines
- Experience processing video or sensor data at scale: large binary formats, streaming ingestion, distributed batch processing, object storage economics
- Fluency in Python and comfortable with AWS
- Genuine data taste: you can look at a sensor trace or a timing histogram and tell when something is off
- Comfort in ambiguous, fast-moving problem spaces where requirements evolve with the customer
Nice to Have- Experience with robotics data formats and tooling (MCAP, ROS bags, protobuf, Foxglove), camera geometry, or multi-sensor calibration and synchronization
- Computer vision or multimodal ML experience (detection, tracking, VLM-based labeling or QC)
- Prior work on data engines for AV, robotics, or egocentric video
Benefits- Bi-annual performance bonus structure
- Generous equity grant vested over 4 years
- Up to $15k Relocation bonus
- $10K housing bonus (if you live within 0.5 miles of our office)
- $1.5K monthly stipend for meals
- Free Equinox membership
- $200 monthly laundry reimbursement
- $200 monthly personal wellness reimbursement
- Health, Dental, Vision insurance
