Software Engineer, Robotics Data
Role Overview
This senior-level role involves building the end-to-end data pipeline for physical-world sensor data (video, depth, IMU, audio) at petabyte scale. You'll design automated QC, dataset versioning, and privacy redaction, integrating VLM-assisted pre-labeling into production workflows. As a founding engineer on a strategically central product, you'll directly shape the data standards that frontier AI labs rely on.
Perks & Benefits
The role offers bi-annual performance bonuses, generous equity, and a $1.5K monthly stipend for meals. Remote work is supported, with relocation and housing bonuses available if you choose to live near an office in San Francisco, NYC, or London. Additional perks include free Equinox membership, laundry and wellness reimbursements, and health/dental/vision insurance.
Full Job Description
About Mercor
Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
About the Role
Frontier 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
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