Meta is seeking a Robotics Engineer to join our Infra Robotics team. This team implements advanced robotics technologies to enable efficient and safe data center operations.The logistics robotics engineer is responsible for integrating robotics hardware and software into Meta’s data center logistics. This includes solution architecture, requirements gathering, system integration, verification and validation, concept of operation (ConOps), product release (including site acceptance testing), and post-release support. The role involves close collaboration with software, hardware, and logistics partners to optimize operational efficiency and reduce risks across Meta’s global infrastructure.
Seeking significant experience across the product development lifecycle—from product design and development to system integration, verification, and product release—focused on robotics and large-scale robotics. This includes applications such as warehouse, fulfillment center, and “factory 4.0” automation.
Hands-on experience with large-scale automation systems, including relevant workflows, automation analysis software (for simulating factories, automating processes, and analyzing manufacturing workflows), and direct AGV experience is expected. Understanding of robotics technologies—covering sensing, planning, navigation, decision-making, and robot manipulation—plus hands-on troubleshooting skills.
Responsibilities
- Partner with infrastructure and logistics teams to understand operational requirements and identify opportunities for robotics and automation to improve efficiency and safety
- Translate customer and operational needs into actionable product requirements and technical specifications. Make tradeoffs between software and hardware solutions, and drive build-versus-buy decisions
- Collect, analyze, and interpret data center operational workflows using advanced tools to drive automation requirements and quantify risks and opportunities
- Lead the design and implementation of robotic solutions for material handling (inventory movement, equipment transport, automated storage/retrieval) with internal and external partners
- Lead software and hardware architecture reviews to identify and address gaps in solution design, ensuring performance and scalability of both software and hardware systems
- Drive proof-of-concept development and evaluation, building and testing prototypes to validate feasibility and operational improvements
- Conduct rigorous testing and validation of software modules and systems, employing simulation tools and real-world testing scenarios to verify functionality, performance, and safety requirements
- Create engineering development plans and milestones, coordinating cross-functional teams to deliver R&D milestones on time and with high quality
- Develop and execute testing strategies, leading QA/QC to verify and validate robotic solutions against product specifications and customer requirements
- Lead root cause analysis for product failures, communicating findings and driving mitigation and improvement plans with partners
- Define product release processes (field pilots, site acceptance testing, operational workflows, software version control) and post-release support strategies
- Create and maintain product and technology roadmaps to drive ongoing innovation
- Develop industry relationships with other data center peers and external organizations to remain current on industry trends and future directions
- Visit data center sites for engineering studies, robotics systems audits, and collaborations with local subject matter experts
- 15% domestic and/or international travel required to Meta Data Centers/offices
Minimum Qualifications
- Technical troubleshooting and data analytics skills
- Effective communication, leadership, organizational, engineering, and program management skills
- 5+ years in large-scale automation at factories, fulfillment centers, or similar industries using AGVs or similar robotic platforms
- Familiarity with product field operational workflows
- Experience coding in higher-level languages (e.g., Python, PHP, or C++)
- Familiarity with hardware/software development and system integration for automation solutions
- Familiarity with QA/QC testing (functional, use-case, stress, regression) and release processes
- Comprehensive understanding of robotics principles and concepts, including perception, motion planning, and control
- 10+ years of experience in end-to-end management and product release of material flow solutions
- Experience building cross-functional relationships and influencing stakeholders at all levels, including policies and procedures for robotics integration
- Expertise in relevant safety standards for material handling and logistics automation
- B.S. or M.S. in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, Robotics, or equivalent experience
- Familiarity with software version control and branching for medium-scale deployments
- Mentorship experience for team members in product development and process improvement
- Proven experience in collecting, analyzing, and interpreting operational workflows to drive automation requirements
- Experience navigating ambiguity, pioneering new technology adoption, and deploying products for field operational success Hands-on system engineering and architecture experience across the full product lifecycle (definition, requirements, specification, design, integration, QA, NPI, field deployment, operations)
- Knowledge of robotics technologies (sensing, planning, navigation, decision-making, robot manipulation, ROS, machine learning)
- Experience in large/complex system design (robotics, industrial automation, consumer electronics)
- Experience designing and building automation and tooling for operational workflows
- Understanding of system interactions (hardware, software, firmware, frameworks, network, latency, interfaces)
- Master’s in a relevant field
- Experience standardizing incident response and crisis management plans
- Familiarity with data center technology stack (compute, network, storage, software architectures)
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies