Senior AI/ML Delivery Leader (Generative AI)

T-Mobile US Inc.; Frisco (TX); On-site; USD 172,000 - 311,000; Full time

Job summary

The Sr Manager, Machine Learning at T-Mobile leads the strategy, architecture, engineering, and production delivery of AI, ML, and Generative AI solutions that advance business outcomes and customer experiences. This leader translates opportunities into scalable, secure, reliable AI capabilities across teams and partners, guiding full lifecycle from design to deployment.

Responsibilities include setting technical direction, mentoring engineers, managing budgets, and enforcing responsible AI

Qualifications

• Bachelor's degree in a relevant field.
• 7+ years of leadership in ML/Data Science preferred.
• 4-7 years in data querying and feature engineering in cloud environments.
• Experience deploying ML solutions end-to-end.

Responsibilities

• Lead AI/ML projects from strategy to production.
• Coordinate cross-functional teams to integrate models into operations.
• Make decisions on team development, resources, and budgets.
• Collaborate with departments to ensure secure, scalable implementations.
• Define AI engineering standards and governance.
• Evaluate outcomes and adjust strategies to evolving tech trends.

Skills

Leadership

Strategy

Collaboration

Project Management

Innovation

Engineering

Generative AI

LLM Engineering

MLOps / LLMOps

Responsible AI

Education

Bachelor's Degree

7+ years team leadership in ML/DS

Experience with cloud platforms (AWS/Azure/GCP)

Data mining / ML deployment

Tools

AWS

Azure

Google Cloud

CI/CD for ML

Model evaluation & monitoring

Job description

The Sr Manager, Machine Learning at T-Mobile leads the strategy, architecture, engineering, and production delivery of AI, ML, and Generative AI solutions that advance business outcomes and customer experiences. This leader translates opportunities into scalable, secure, reliable AI capabilities across teams and partners, guiding full lifecycle from design to deployment.

Responsibilities include setting technical direction, mentoring engineers, managing budgets, and enforcing responsible AI