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Robotics Data Engineer

Job in Warren, Macomb County, Michigan, 48091, USA
Listing for: Veriipro
Full Time position
Listed on 2026-05-28
Job specializations:
  • IT/Tech
    Robotics, AI Engineer, Data Engineer, Machine Learning/ ML Engineer
  • Engineering
    Robotics, AI Engineer, Data Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Job Summary

We are seeking a Robotics Data Engineer with strong experience in machine learning data pipelines, robotics perception systems, and multimodal datasets. The ideal candidate will build scalable data infrastructure to support robotic vision, grasping, manipulation AI, and simulation-to-real (Sim2

Real) workflows.

This role requires hands-on Python development, production ML pipeline experience, robotics simulation exposure, and collaboration with cross-functional AI and robotics teams.

Required Technical / Functional Skills
  • 3+ years of experience in Data Engineering, Machine Learning Systems, Robotics, or related fields
  • Experience building production-grade ML/AI data pipelines
  • Strong Python programming skills (data processing & pipeline development)
  • Experience handling large-scale multimodal datasets (vision, depth, tactile, sensor data)
  • Direct experience supporting robotics perception, grasping, or manipulation AI
  • Familiarity with robotics simulation platforms (e.g., Isaac Sim)
  • Experience with synthetic data generation and Sim2

    Real workflows
  • Experience with data labeling tools and annotation workflows at scale
  • Hands-on knowledge of Tensor Flow and/or Py Torch
  • Experience with Microsoft data ecosystem (Azure data services, Power BI)
  • Exposure to self-supervised or weakly supervised learning techniques
  • Strong collaboration and systems-thinking mindset
Roles & Responsibilities
  • Design and implement scalable data pipelines for robotic vision and sensor datasets
  • Build infrastructure for high-throughput data capture from robots and simulation environments
  • Develop semi-supervised and self-supervised data labeling workflows
  • Enable Simulation-to-Real (Sim2

    Real) data workflows including domain randomization
  • Manage dataset versioning, metadata, and data governance for ML model training
  • Collaborate with Robotics Perception, Grasping AI, and Simulation teams
  • Establish and monitor data quality metrics aligned with AI model performance
Technologies / Environments
  • Python
  • Machine Learning Data Systems
  • Tensor Flow / Py Torch
  • Robotics Perception & Manipulation AI
  • Isaac Sim (or similar simulation platforms)
  • Azure Data Services
  • Multimodal Robotics Datasets
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