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Job Overview
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 business opportunities into scalable, secure, reliable, and responsible AI capabilities, including predictive models, large language model (LLM) applications, retrieval-augmented generation (RAG), intelligent agents, and AI-enabled automation. The role directs multi-functional engineering teams and partners across product, data, cloud/platform engineering, cybersecurity, privacy, legal, and business organizations to move solutions from experimentation to production and sustain them through the full lifecycle. Responsibilities include technical direction, talent development, resource and budget planning, engineering standards, model and application evaluation, operational monitoring, and continuous improvement. By aligning AI engineering investments to enterprise priorities and measurable business value, this role strengthens T-Mobile's innovation, operational efficiency, and long-term technology capabilities.
Job Responsibilities :
Leads the strategic implementation and operational management of AI and ML projects, ensuring alignment with organizational goals
Coordinates multi-functional teams to integrate AI/ML models into business operations, enhancing efficiency and innovation
Manages critical decisions related to team development, resource planning, and budget allocation
Collaborates with various departments to ensure seamless operation and implementation of AI and ML technologies
Drives advancements in technological capabilities through effective leadership and strategic oversight
Evaluates project outcomes and adjusts strategies to meet business needs and technological trends
Defines and governs end-to-end AI engineering practices for design, development, evaluation, deployment, monitoring, security, reliability, and lifecycle management of production AI/ML and Generative AI solutions.
Leads the architecture and delivery of scalable AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG), AI agents, and workflow automation, selecting approaches based on business value, risk, and technical fit.
Establishes engineering standards and measurable outcomes for AI quality, safety, privacy, fairness, latency, cost, availability, and business impact; communicates delivery risks, trade-offs, and results to executive and cross-functional stakeholders.
Education and Work Experience :
Bachelor's Degree and 7 years of related work experience OR combination of education and experience deemed equivalent (Required)
7-10 years Experience leading and managing a team in the field of machine learning or data science (Preferred)
4-7 years Experience with data querying, wrangling, cleaning, and feature engineering in big data environments such as AWS, Azure, and Google Cloud (Preferred)
4-7 years Experience building and deploying data mining, visualization, statistical modeling, and machine learning solutions using various supervised/unsupervised ML algorithms (Preferred)
Knowledge, Skills and Abilities :
Leadership Strong leadership skills with the ability to lead and inspire cross-functional teams. (Required)
Strategy Exceptional strategic thinking and problem-solving abilities, with a deep understanding of AI/ML technologies and applications. (Required)
Collaboration Excellent communication, negotiation, and interpersonal skills…