General Motors
Staff Data Scientist - AI Engineering & Productivity
Austin, Texas, United States of America +1 · Hybrid · Staff · Full-time · Posted Oct 8, 2026
- Location
- Austin, Texas, United States of America
Warren, Michigan, United States of America - Experience
- 8+ years working with and 3+ years leading; preferred: 10+ years working with and 6+ years leading.
- Education
- M.S. degree in operations research, engineering, computer science, applied statistics, physics, or related field. Equivalent additional experience may substitute for an advanced degree. Ph.D. preferred.
- Visa sponsorship
- GM does not provide immigration-related sponsorship for this role; applicants who need GM immigration sponsorship now or in the future should not apply.
About the job
Leads AI/ML and data science products that deliver secure, production-grade tools and measurable productivity gains across engineering workflows and the product lifecycle.
What you'll do
- Set scientific direction and ensure methodological quality and operational robustness for owned products.
- Lead product delivery, managing timelines, budgets, risks, and measurable business impact.
- Collaborate across technical and business teams, mentor scientists, and translate technical tradeoffs into business decisions.
What they ask for
- 8+ years working with and 3+ years leading advanced analytics, AI/ML and/or operations research initiatives.
- Expertise across multiple AI/ML and analytics domains, with demonstrated thought leadership in innovative methods.
- Expertise in Python and cloud-based data science platforms; proficiency in SQL.
- M.S. in a related field; equivalent additional experience may substitute for an advanced degree.
Nice to have
- Databricks; generative AI tools and platforms such as Cursor, GitHub, Microsoft Copilot, Glean, or Databricks Genie.
- 10+ years working with and 6+ years leading relevant initiatives; Ph.D. or external technical recognition.
Tools
LLMs, Python, Databricks, SQL, Cursor, GitHub, Microsoft Copilot, Databricks Genie
AI focus
Develop and lead production-grade AI/ML and data science products, including work involving LLMs and generative AI, to improve engineering productivity and decision-making.
Model-written summary · the original posting is authoritative