Software Engineer, Robotics Data
San Francisco, California, United States
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingFrontier AI is going physical, and the labs building it are bottlenecked on one thing: high-quality data from the real world.
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.
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
Build shared processing components such as privacy redaction, transcription, encoding, format packaging across all offerings
From the employer’s posting
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
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
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
Tools in this posting
- Python
- AWS
Source — Tool mentions in context
- 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
Benefits in the posting
Full benefits wording- 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 personal wellness reimbursement
- Health, Dental, Vision insurance
From the employer’s posting.
About Mercor
Mercor's mission is to organize human intelligence to power the AI economy.
In the employer’s words · Read in context
Job description
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
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
San Francisco, California, United States
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- Work authorization
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- Status in our records
- Active
- First seen by us
- Jul 29, 2026
- Recorded sightings
- 3
- Last seen by us
- Sep 30, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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