Lead Robotics Data Engineer

Voxelmaps is building the data infrastructure layer for Physical AI and humanoid robotics. As robots move from controlled environments into the real world, the bottleneck is not model capability alone — it is the ability to produce large volumes of repeatable, well-documented, multimodal human task data. We are building the operation that solves that.

The Lead Robotics Data Engineer owns the technical soul of the operation: designing how data is captured, setting the standards every dataset must meet, and translating those standards into protocols a scaled team in Juárez can execute reliably.

This is not a research role and not a pure engineering role. It sits at the intersection of both: hands-on experimental design, rigorous data standards, and the operational discipline to make a cross-border collection pipeline actually work.

Responsibilities:

>Experiment Design:

• Author capture protocols for human task, manipulation, navigation, and interaction datasets
• Define dataset schemas, metadata standards, versioning conventions, and acceptance criteria for every dataset family
• Run 20–100 pilot demonstrations per task family in El Paso, review failure modes, and iterate

>Capture Operations:

• Operate egocentric (head/chest-mounted), exocentric multi-camera, motion capture suit, and UMI-style demonstration rigs
• Calibrate and maintain all sensor systems before each capture session
• Implement and refine human teleoperation setups as the program matures

>Cross-Broder Handoff:

• Convert El Paso pilot protocols into operator-ready SOPs for the Juárez scaled capture team
• Train Juárez Supervisor on SOPs, certify the capture process, and approve equipment kits
• Monitor protocol drift and recertify operators as dataset families evolve

>Model Testing & QA:

• Support training and evaluation of VLMs and VLAs on robot arms and other platforms in El Paso
• Close the loop between data collection and model evaluation outcomes — stop collecting low-value data quickly
• Chair weekly protocol review: new task families and failure analysis

>Data Pipeline Oversight:

• Collaborate with the Data Engineer / MLOps to build ingestion, versioning, metadata integrity, and dataset packaging workflows
• Monitor metadata completeness and time-from-capture-to-packaged-dataset KPIs
• Contribute to partner-grade dataset documentation and train/validation splits

>Reporting & Communication:

• Present experimental findings internally and to external partners
• Produce technical reports and maintain a clear dataset release log
• Contribute to talks, demos, and video presentations as Voxelmaps grows its external profile

Engineer Profile Requirements & Qualifications:

• Hands-on robotics experiment design & protocol authorship
• Capture architecture: egocentric, exocentric, mocap, UMI-style
• Python — strong, production-quality scripting
• ROS / ROS2 — practical experience
• Dataset standards: metadata schemas, versioning, QA acceptance criteria
• Ability to translate protocols into Juárez operator-ready SOPs
• Cross-functional communication: engineers, operators, partners
• Self-directed; owns outcomes without close supervision

Additional Qualifications That Can Drive Success In This Role:

• Responsible for interviewing, selecting, and building the robotics division. This division will consist of two teams (experimentation research and definition team and data acquisition team); assumes full ownership of team performance, execution, and overall success
• MSc in Robotics, CS, Mechanical Engineering, or related (strong industry background accepted)
• Imitation learning / robot learning pipeline experience
• Human teleoperation system operation
• Familiarity with open-source VLM/VLA models (LLaVA, OpenVLA, RT-X)
• Motion capture suit calibration & management
• Experience with humanoid robot platforms
• Prior experience writing training or QA documentation for operators

For Success In This Role:

After 3 months in the role, this hire will be considered successful if:

• Three protocol families are running with documented SOPs and measurable acceptance criteria
• Pilot datasets have been reviewed and validated against quality standards
• Juárez Supervisor has been trained and certified on at least one protocol
• Operating dashboard shows stable throughput and first-pass acceptance rate trends
• Data Engineer / MLOps has a clear and usable ingestion and packaging pipeline to work against

What We Offer:

• First technical hire: architect the data factory, not just operate it
• Work at the frontier of Physical AI and humanoid robotics
• Partner access to some of the largest technology and robotics companies in the world
• Hands-on with robot arms, motion capture, and multimodal AI pipelines
• Meaningful equity in a company building the data infrastructure layer for Physical AI
• Direct line to VP of Data Collection — decisions made quickly, no layers

*Job Type:* Full-time, Internal Employee

*Reports To:* *Director, Robotics and Data Acquisition*

*Pay:* *$110,000-130,000 (depending on experience) yearly salary, paid semi-monthly*

*Location:*

• El Paso, TX – Office based. (Required)
• Relocation may be offered for the right candidate
• Must be able to commute to office daily

*Travel:* *Some travel may be required*

DO NOT CONTACT THE HIRING MANAGER DIRECTLY, YOU MUST FOLLOW THE APPLICATIONS PROCESS

EEO Statement: Voxelmaps is an equal opportunity employer. All qualified applicants will receive consideration for employment. Supplier shall not discriminate against any worker based on age, disability, ethnicity, gender, marital status, national origin, political affiliation, color, race, religion, sexual orientation, gender identity or expression, union membership, protected veteran status, genetic information, or any other status protected by country law, in hiring and other employment practices. Supplier shall not require pregnancy or medical tests, except where required by applicable laws or regulations or prudent for workplace safety, and shall not improperly discriminate based on test results.

Disclaimer: All claims and offers to compensation, rewards, and onboarding procedures are at the sole discretion of the client and not that of the consulting firm.