At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That's how we're UNSTOPPABLE for our employees! The Principal Architect, Machine Learning Solutions (ML), is responsible for developing innovative solutions and technology strategies specifically focused on machine learning (ML) systems. This role involves architecting and building end-to-end solutions for coding, deploying, and maintaining large-scale ML models throughout their lifecycle. The Principal Architect will partner with other senior architects and stakeholders to make recommendations for new procedures and overall architectural approaches, focusing on integrating ML models into scalable, reliable, and maintainable systems. Responsibilities: Strategy Own solution design for multiple cross domain initiatives and works across domains to ensure cohesive solution. Review and identify the gaps in the architecture and solution designs, assesses and defines remediation efforts or mitigation options. Drive to practical solutions considering all teams, initiatives and long-term outlook. Make and implement complex decisions aimed at improving the quality, effectiveness or ability to achieve revenue, profitability and strategic goals for the organization. Work with data science leaders to define and implement the vision of data and AI. Innovation and Leadership Lead the overall technical design and end-to-end solution design for assigned initiatives. Ensure quality, consistency, and alignment of designs to TMUS standards and digital strategy. Lead large cross-domain initiatives supported by E2E Design, applies digital standards to project Solution Architecture, drives Technical Strategy, and architectural tradeoff discussions. Balance constraints in IT, business, and delivery to deliver optimal architecture for an initiative. Lead design orchestration on large-sized initiatives or work streams. Provide input into the definition of Digital Architecture standards as they are created. Mentor junior ML Engineering teams based on a scalable set of best practices. Establish processes and standard methodologies to train and develop ML Engineering teams. Technology and System Own technical solutions on cross-domain initiatives. Develops innovative solutions and technology strategy. Owns E2E solution design strategy across teams. Author artifacts such as Concept Architecture, Top 25 System Impacts, and E2E Solution Architecture documents. Support the definition and adoption of common software development processes. Prepare and maintain design deliverables, including architecture diagrams, data models, and API/micro-service architecture. Enforce design process standards on assigned initiatives. Write advanced documentation, including architecture, capabilities, limitations, and advantages for technologies. Routinely create and present executive and external materials, including white papers. Actively contribute to industry publications and professional forums. Relationship, People Management, and Project Management Interacts with senior management to shape and align solutions against desired minimum viable product scope. Applies a broad understanding of products, systems, and technologies across the business portfolio and deep technical ability on integration of these components to deliver a cohesive E2E solution architecture for a given initiative. Translates business requirements into technical requirements that the system analysts and other technical team members drive into the project design and delivery Qua