LATAM Operations Lead

Posted Yesterday
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Hiring Remotely in México
Remote
Mid level
Artificial Intelligence • Machine Learning • Robotics • Software
The Role
Leads the build-out and operation of XDOF’s LATAM robotics data-collection network in Mexico or Brazil. Responsibilities include expanding collection venues, sourcing partnerships, recruiting and managing field teams, deploying and maintaining hardware, optimizing operational efficiency, monitoring data quality, and converting market learnings into reusable SOPs and playbooks.
Summary Generated by Built In

Role Mission
Own the build-out of XDOF’s ground-level data acquisition operation in LATAM (Mexico/Brazil), taking the region to a fully operating, self-auditing local network. This role owns the end-to-end pipeline of securing high-fidelity physical-world data (Egocentric, Teleoperation, etc.) — from signing individual high-value venues to institutionalizing multi-scenario local partnerships.
Location:
Based in Mexico or Brazil.
Responsibilities

  • Data collection scene expansion: Own the ground-level expansion strategy and 0-1 execution to build an expanding pipeline of robotics data collection - developing and closing a diversified network of data collection venues and access points (retail, logistics, industrial, urban, etc.)

  • Team Building & Management: Recruit, train, and manage data collection execution teams. Establish SOPs to ensure data integrity and operational velocity.

  • Efficiency Optimization: Monitor offline operational data to optimize workflows and staffing, controlling cost per usable hour while maximizing output.

  • Hardware management: manage the deployment, maintenance and calibration of multi-modal data collection hardware.

  • Operational Optimization and Feedback: Monitor offline operational data to optimize workflows and staffing, provide clear operational feedback to central teams; document market learnings as SOPs/playbooks for reuse in future markets.


Qualifications

  • 3–5+ years of experience managing field operations, growth, or ground execution for major tech platforms, IoT companies, or hardware-enabled startups.

  • Proven track record of sourcing, onboarding, and managing SME partnerships and vendor networks (Required).

  • Working proficiency or fluency in Spanish, Portuguese, or other target-market languages is highly preferred.

  • Solid grasp of Embodied AI and machine learning data fundamentals (e.g., Teleoperation workflows, Egocentric/First-Person vision requirements) with the ability to translate technical data specifications into field operational blueprints.

  • A resilient, "builder" mindset with a high tolerance for ambiguity, comfortable traveling frequently and executing directly in unstructured or high-friction environments.

  • Strong cross-functional capability, matching analytical funnel management (SQL/Excel, conversion rates) with high-stakes, face-to-face field negotiation.

Skills Required

  • 3-5+ years of experience managing field operations, growth, or ground execution for major technology platforms, IoT companies, or hardware-enabled startups.
  • Proven experience sourcing, onboarding, and managing SME partnerships and vendor networks.
  • Working proficiency or fluency in Spanish, Portuguese, or another target-market language.
  • Working knowledge of Embodied AI and machine learning data fundamentals, including teleoperation workflows and egocentric or first-person vision requirements.
  • Ability to translate technical data specifications into field operational blueprints.
  • Resilient builder mindset with tolerance for ambiguity and comfort traveling frequently in unstructured or high-friction environments.
  • Strong cross-functional capability combining analytical funnel management using SQL or Excel with face-to-face field negotiation.
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The Company
Year Founded: 2024

What We Do

XDOF is the infrastructure partner for the world's most ambitious robotics builders, developing the tools, data, and services that accelerate the future of physical AI. They build the foundational infrastructure for robotics foundation models, including data collection systems, annotation pipelines, and exabyte-scale data infrastructure, helping frontier labs build general-purpose robots by solving the critical bottleneck of high-quality training data.

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