Software Engineer, Robotics

Reposted 19 Days Ago
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.

As a Software Engineer on Robotics, you'll sit between Mercor's data systems and our customers' infrastructure. Every frontier lab wants something different: container format, schema, fields, and quality requirements. You'll build infrastructure general enough that a new customer becomes a quick configuration, and you'll work directly with customer engineering teams on bespoke requests, feeding what you learn into scalable platform architecture decisions. An example might be modifying the segmentation model derived from a customer request for stricter filtering on hands being in frame and building this into a configurable pipeline feature.

Prior robotics experience is not required. This is a backend and data engineering role at its core, developing pipelines, formats, and storage methods. If you've built high-volume data infrastructure anywhere and want depth in robotics data and directly, working directly with the engineers and researchers at the labs and robotics companies building physical AI, this role is for you.

What You'll Do
  • Own the reusable infrastructure behind robotics data deliveries: the processing, packaging, and delivery systems

  • Format and transform datasets to per-client specification: MCAP and other container formats, custom schemas, field mappings, metadata, and versioning

  • Work directly with customer engineering teams to scope and build bespoke schemas, custom fields, and one-off transforms where requirements are custom

  • Build and operate the pipelines that move data from Mercor's systems into customer storage reliably at petabyte scale

  • Partner with operations and product to turn evolving requirements into shipped data deliveries, and prototype quickly when a new data type or customer arrives

  • Build automated validation techniques

What We're Looking For
  • Strong backend and data engineering fundamentals in a modern language (Python, Go, Rust) and comfort operating production systems on AWS and GCP

  • Experience building and owning high-volume data pipelines, not just contributing to them

  • Experience with large binary formats, streaming ingestion, distributed batch processing, and object storage economics

  • Customer-facing instincts: you can lead a technical conversation, ask the right questions, and push back when a request is unreasonable

  • Comfort working through ambiguity and shipping iteratively with a product team, where requirements evolve with the customers and data types

Nice to Have
  • Experience with robotics/AV data formats and tooling such as MCAP, ROS, protobuf, Foxglove

  • Prior work on data engines, pipelines, or delivery for multimodal data

  • Multi-sensor data experience across video, depth, inertial, and audio, including calibration and synchronization

  • Forward-deployed, solutions, or delivery engineering experience at a data or infrastructure company

  • Computer vision or multimodal ML exposure: detection, tracking, or VLM-based labeling and QC

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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