Senior Robotics Data Engineer/Data Scientist

General Motors (GM)

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Warren, MIAustin, TX
Salary
$125,000–$168,650 / yr
Posted
24 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $188k
This role $147k
$113k most similar roles pay here $237k

This role pays less than 78% of similar roles. Most pay $151,875–$223,750 — the shaded band above. At the midpoint, this role pays about $147k versus about $188k for comparable roles.

Based on 240 similar postings.

Employer

About General Motors (GM)

General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.

General Motors (GM) currently has 116 open roles on FindRole.

Listed pay typically runs $160,200–$245,000 across 59 roles with salary data.

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View all roles at General Motors (GM)

At a glance

TL;DR · Senior Robotics Data Engineer/Data Scientist

Senior Robotics Data Engineer/Data Scientist joins the manufacturing data organization to build the data and data science backbone for scalable robotics intelligence across manufacturing environments. This individual contributor role involves designing, building, and maintaining end-to-end solutions for robotics data ingestion, processing, storage, and analysis. The candidate will develop scalable pipeline architectures for multimodal robotics data including sensor streams, telemetry, images, and time series while creating high-quality analytic datasets to support model development and production monitoring. Required skills include proficiency in Python and at least one other language like Java, C++, or Scala, alongside experience with big data tools such as Hadoop, Spark, Kafka, and PostgreSQL. The role focuses on transforming raw robotics behavior into actionable insights through machine learning, MLOps workflows, and automated infrastructure to solve complex manufacturing and operational challenges.

What you'll do

  • Design and maintain end-to-end data solutions for robotics data ingestion, processing, storage, and visualization.
  • Build and optimize scalable data pipeline architectures for multimodal robotics data including sensor streams and telemetry.
  • Develop high-quality analytic datasets to support business intelligence, model development, and production monitoring.
  • Apply machine learning and statistical analysis to identify patterns and improve system performance.
  • Translate complex robotics behaviors and failure modes into curated datasets and actionable insights.
  • Implement MLOps workflows including data versioning, lineage, and experiment tracking for reproducible analytics.
  • Build internal tools, APIs, and logical data models to improve data governance and scalability.
  • Drive infrastructure improvements through automation and the establishment of high engineering standards.

What we're looking for

  • Bachelor's degree in Computer Science, Data Science, Robotics, Engineering, or a related technical field.
  • 5+ years of professional experience in data engineering, software engineering, machine learning engineering, or applied data science.
  • Strong programming skills in Python and at least one other language such as Java, C++, or Scala.
  • Experience building production-grade data pipelines, backend services, APIs, and full stack data applications at scale.
  • Hands-on experience with big data, streaming, and distributed systems technologies like Hadoop, Spark, Kafka, or PostgreSQL.
  • Experience with cloud platforms, data orchestration frameworks, and data modeling for analytics and machine learning.
  • Experience applying data science or machine learning techniques to real-world engineering or operational problems.
  • Strong software engineering fundamentals including version control, testing, CI/CD, documentation, and automation.
  • Advanced degree in Data Science, Robotics, Computer Science, or a related field (preferred).
  • Experience with robotics, autonomous systems, industrial IoT, or manufacturing analytics (preferred).
  • Hands-on experience with ROS/ROS 2, robotics telemetry, logging, replay, or simulation data workflows (preferred).
  • Experience with machine learning lifecycle and data quality tooling (preferred).
  • Familiarity with data governance, lineage, auditability, and reproducibility in regulated environments (preferred).
  • Experience mentoring engineers or setting technical direction on complex initiatives (preferred).

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