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.
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. You'll work alongside operations and product teams to turn a set of requirements into a working delivery pipeline: the schema, fields, format, transport, and quality checks that prove what shipped is what was specified.
This is a delivery-focused applied engineering role, not a classic robotics role. You will learn to grow and deeply understand robotics data types and work as part of a critical team leading the frontier development of physical AI, collaborating with engineers and researchers at frontier labs to ensure the data gets delivered properly.
Partner with SPLs and client engineering teams to translate and implement data requirements into concrete delivery pipelines
Build and operate the pipelines that move data from Mercor's systems into customer storage reliably at petabyte scale
Format and transform datasets to per-client specification: MCAP and other container formats, custom schemas, field mappings, metadata, and versioning
Build automated validation to support delivery pipelines
Prototype quickly against new customer requirements, and debug issues when needed
Turn one-off client requests into reusable components, and own delivery infrastructure end to end
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
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
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
Job details are sourced from the employer's original posting.
Open job postingAbout the company
Mercor is scaling quickly, and focused on building and developing a world-class people organization.