Staff AI Engineer - Remote, Scalable AI Platforms

General Motors; Warren (MI); Remote; USD 150,000 - 190,000; Full time

Job summary

General Motors is seeking a Staff AI Engineer to design and deliver trustworthy AI systems, ML solutions, data products, and applications across Sales, Service, Marketing, and Global Markets. This hands-on IC role encompasses problem framing, data engineering, model development, and production operation at scale.

The role combines practical data science with strong software engineering, delivering reusable, secure, and observable AI capabilities.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field; advanced degree preferred.
• 8+ years of professional experience across artificial intelligence, machine learning, data science, data engineering, software engineering, application development, or a closely related discipline.
• Demonstrated experience taking AI, machine-learning, analytics, or data-product solutions from problem definition and proof of concept through production deployment and ongoing operation.
• Strong proficiency in Python and SQL, including production-quality code, testing, version control, documentation, and debugging.
• Hands-on experience with data-science and machine-learning libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, or equivalent technologies.

Responsibilities

• Translate ambiguous business problems into clear AI objectives, solution strategies, evaluation plans, and measurable success criteria.
• Develop, validate, and improve predictive, forecasting, classification, segmentation, optimization, natural-language, generative-AI, and decision-support solutions.
• Define data requirements and partner with data engineering, platform, and business teams to establish reliable, documented data sources.
• Build scalable ingestion, transformation, aggregation, feature, embedding, and knowledge pipelines using batch or streaming patterns.
• Create reusable data products, analytical datasets, semantic models, feature assets, and retrieval indexes.
• Build production-grade AI applications, services, APIs, dashboards, and workflow tools that make AI capabilities accessible to end users.
• Translate models and AI systems into intuitive user experiences, decision-support tools, automation workflows, and self-service capabilities.
• Design clean interfaces between data pipelines, models, foundation models, tools, backend services, and front-end or workflow applications.
• Implement retrieval, grounding, tool use, orchestration, prompt management, evaluation, and human-in-the-loop patterns where appropriate.
• Develop secure, testable, observable, and maintainable software using sound engineering practices, code review, version control, and automated testing.
• Partner with architects and software engineers on application structure, integration patterns, authentication, authorization, deployment, and operational support.
• Establish evaluation frameworks that reflect real-world business outcomes, not only offline metrics.
• Design monitoring for data quality, drift, model performance, latency, and business outcomes.
• Investigate production issues and improve models and pipelines through structured iteration.
• Apply responsible-AI, privacy, security, and data-governance principles throughout design and operation.

Skills

Python

SQL

Data science

Machine learning

Software engineering

Education

Bachelor’s degree in CS/Data Science/Engineering

Advanced degree preferred

Tools

Databricks

Azure AI Foundry

PyTorch

TensorFlow

Spark/PySpark

REST APIs

Git

Job description

General Motors is seeking a Staff AI Engineer to design and deliver trustworthy AI systems, ML solutions, data products, and applications across Sales, Service, Marketing, and Global Markets. This hands-on IC role encompasses problem framing, data engineering, model development, and production operation at scale.

The role combines practical data science with strong software engineering, delivering reusable, secure, and observable AI capabilities.