Senior Robotics Data Engineer

Compunnel, Inc.; Michigan; On-site; USD 100,000 - 130,000; Full time

Job summary

A technology firm in Michigan is seeking a Senior Robotics Data Engineer to support large-scale robotics initiatives through design and implementation of advanced data systems. The ideal candidate will have over 3 years of experience in data engineering and robotics, with a strong background in Python and machine learning systems. This role involves building data pipelines and collaborating with various teams to ensure efficient data workflows. Competitive salary and benefits offered.

Qualifications

• 3+ years of experience in data engineering or related fields.
• Strong hands-on experience with Python-based data tooling.
• Experience building production-grade data pipelines for ML/AI systems.

Responsibilities

• Design and implement scalable data pipelines for large-scale robotic datasets.
• Build infrastructure for high-throughput data capture.
• Develop and deploy self-supervised data labeling workflows.

Skills

Data engineering

Machine learning systems

Robotics

Python

Cross-functional collaboration

Education

Master’s degree in Engineering, Computer Science, Data Science or equivalent practical experience

Tools

Isaac Sim

Data labeling pipelines

Job description

The Senior Robotics Data Engineer supports large-scale robotics initiatives by designing and implementing end-to-end data systems that enable generalized and scalable AI perception and grasping models.

This role is part of an advanced development team focused on powering robotics capabilities through real-world and simulated data workflows.

The engineer will build and maintain robotic data pipelines, support high-throughput data capture, enable annotation and synthetic data generation processes, and manage datasets used for training and evaluating AI models across diverse manufacturing contexts.

Key Responsibilities

• Design and implement scalable data pipelines for large-scale robotic datasets, including vision, depth, tactile, and force/torque data.
• Build infrastructure to support high-throughput data capture from real robots and simulation environments.
• Develop and deploy semi-supervised or self-supervised data labeling workflows to reduce manual annotation costs.
• Enable simulation-to-real (Sim2Real) workflows through domain randomization and synthetic data generation.
• Own data versioning, metadata management, and dataset governance to support model training, evaluation, and regression testing.
• Collaborate with Robotics Perception, Grasping AI, and Simulation teams to define data requirements and KPIs.
• Support lifecycle management of multimodal robotic datasets.

Required Qualifications

• 3+ years of experience in data engineering, machine learning systems, robotics, or related fields.
• Master’s degree in Engineering, Computer Science, Data Science, or equivalent practical experience.
• Experience building production-grade data pipelines for ML/AI systems.
• Strong hands‑on experience with Python-based data tooling.
• Experience working with large, complex, multimodal datasets.
• Strong systems‑thinking mindset and cross-functional collaboration skills.

Preferred Qualifications

• Experience supporting robotics perception, grasping, or manipulation AI.
• Familiarity with robotics simulation platforms such as Isaac Sim and synthetic data generation workflows.
• Experience working with large-scale annotation tools and data labeling pipelines.