Job Description
At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.
Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.
The Role
We are seeking an Engineer, AI Systems Engineering - Data Science to join our Manufacturing Technology Development team within the General Motors Research and Development organization. In this role, you will create advanced pipelines for capturing, curating, and synthesizing robotic datasets and integrating multimodal sources like tactile, visual, and proprioceptive data. You will innovate in self-supervised data labeling and simulation-to-real transfer. You will provide AI & Simulation teams with rich training resources and Robotics Intelligence teams with high-quality datasets for prototyping.
What You Will Do
Develop data pipelines for multimodal robotic datasets including tactile, visual, and proprioceptive data.
Implement self-supervised data labeling techniques.
Support simulation-to-real data transfer workflows.
Collaborate with AI & Simulation teams to provide training datasets.
Assist Robotics Intelligence teams with prototyping datasets.
Contribute to data engineering best practices.
Your Skills & Abilities (Required Qualifications)
5+ years of experience in data science, machine learning, or engineering.
Bachelor’s degree in Engineering, Computer Science, Data Science, or related field.
Experience with data engineering and machine learning workflows.
Familiarity with multimodal data processing.
Strong problem-solving and collaboration skills.
Proficiency in programming languages such as Python and/or C++.
What Will Give You A Competitive Edge (Preferred Qualifications)
Experience with Microsoft data analysis and database tools, including Power BI.
Knowledge of simulation platforms and data labeling tools.
Experience with Python, TensorFlow, or PyTorch.
Exposure to self-supervised learning techniques.
Strong communication and documentation skills.
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.
Non-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
Accommodations
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