Software Engineer, Robotics Data

Posted Yesterday
San Francisco, CA, USA
In-Office
Mid level
Artificial Intelligence • Software
We use AI to understand human ability and match talent with the opportunities they're best suited for.
The Role
Build end-to-end sensor data pipelines that ingest multi-sensor captures (video, depth, inertial, audio), perform segmentation, pre-labeling, automated QC, privacy redaction, encoding and packaging, and deliver validated, versioned datasets at petabyte scale for frontier AI labs.
Summary Generated by Built In
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

Skills Required

  • Strong production backend/data engineering experience; 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)
  • Fluency in Python
  • Comfortable with AWS
  • Ability to design automated QC for timing/sync integrity, calibration health, sensor continuity
  • Establish dataset schemas, versioning, provenance and traceability
  • Build shared processing components: privacy redaction, transcription, encoding, format packaging
  • Integrate VLM-assisted pre-labeling and quality scoring into production workflows with debuggability and human oversight
  • Genuine data taste; able to detect issues by inspecting sensor traces or timing histograms
  • Comfort working in ambiguous, fast-moving problem spaces with evolving requirements
  • Experience with robotics data formats and tooling (MCAP, ROS bags, protobuf, Foxglove)
  • Experience with camera geometry, 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

Mercor Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Mercor and has not been reviewed or approved by Mercor.

  • Fair & Transparent Compensation Pay is considered competitive across many roles, with clear hourly ranges and an hourly/pay‑per‑task mix designed to align rates with expertise. The structure emphasizes transparent, appropriate pay levels and guarantees payment for legitimate logged time.
  • Strong & Reliable Incentives Payments are processed on a predictable weekly cadence via Stripe/Wise, and some tracks offer additional weekly bonus incentives for top performers. This combination of regular payouts and performance bonuses supports dependable earnings when projects are active.
  • Equity Value & Accessibility Select full‑time roles include generous equity grants alongside cash perks such as relocation and housing bonuses. These elements increase total compensation for those positions.

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The Company
HQ: San Francisco, California
2,217 Employees
Year Founded: 2023

What We Do

We use AI to understand human ability and match talent with the opportunities they're best suited for.

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