Senior ML & AI Scientist: Production-Ready AI Solutions

General Motors; Mountain View (CA); Hybrid; USD 160,000 - 244,000; Full time

Benefits offered by this job

Health benefits

Dental & Vision

Retirement plan

Tuition assistance

GM vehicle discounts

Job summary

General Motors is seeking a Senior Machine Learning and AI Scientist to lead the development and production deployment of advanced ML and AI solutions with measurable business impact.

You will design and implement ML, generative AI, and multi-agent systems across Azure, Databricks, AWS, and GCP, collaborating with business leaders, data engineers, software engineers, and cloud architects to translate needs into scalable AI products.

Qualifications

• 5+ years of experience developing and deploying ML/AI solutions in production.
• Bachelor’s degree in CS/DS/Math/Engineering; advanced degree preferred.
• Experience across cloud platforms (Azure, AWS, GCP).
• Strong ability to communicate technical concepts to nontechnical stakeholders.

Responsibilities

• Identify high-value ML/AI opportunities to improve revenue, cost, risk, and customer experience.
• Translate business objectives into analytical problems with measurable success criteria.
• Design, validate, and deploy production-grade ML models across various use cases.
• Build generative AI and multi-agent solutions coordinating agents, tools, APIs, and workflows.
• Architect cloud-based AI solutions with cross-cloud portability and resilience.
• Mentor other data scientists and engineers in best practices and production discipline.

Skills

Python

SQL

PySpark

ML frameworks

Education

Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or Engineering

Tools

Azure Databricks

Databricks

SageMaker

Vertex AI

TensorFlow/PyTorch

Job description

General Motors is seeking a Senior Machine Learning and AI Scientist to lead the development and production deployment of advanced ML and AI solutions with measurable business impact.

You will design and implement ML, generative AI, and multi-agent systems across Azure, Databricks, AWS, and GCP, collaborating with business leaders, data engineers, software engineers, and cloud architects to translate needs into scalable AI products.