Machine Learning Engineer - AI COE

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The Machine Learning (ML) Engineer focuses on coding, deploying, and maintaining large-scale machine learning models throughout their lifecycle. By combining software engineering principles and data science/machine learning knowledge, the ML Engineer develops the data processes that make ML models generally available for use in products for end-users and customers. The ML engineer should understand machine learning algorithms, have experience in software engineering and various programming languages, including Python, SQL, and Apache Spark. By combining software engineering principles and ML/AI expertise, the engineer builds scalable infrastructure and workflows in modern MLOps environments such as Azure Databricks and GitLab CI/CD. They enable robust experimentation, versioning, and observability using tools like MLflow, LangGraph, and DSPy An understanding of the latest cloud technologies is imperative for the development and deployment of ML solutions as well. The ML Engineer's core value lies in making AI solutions production-ready, performant, and maintainable using cloud-native services and open-source frameworks.

Job Responsibilities:

• Build and maintain full machine learning lifecycles including experiment tracking, model governance, deployment, and monitoring using tools like MLflow, Databricks, DSPy, LangGraph, and Azure DevOps.
• Assemble and transform large, complex datasets from Databricks, PostgreSQL, Apache-based sources, and other structured/unstructured systems, ensuring scalability and performance in production environments.
• Collaborate with data science, ML, and platform teams to build graph-based or modular workflows (e.g., LangGraph), ML pipelines (e.g., in Databricks), and integration with DevOps and GitLab systems.
• Ensure ML models are scalable, reproducible, and well-documented, leveraging MLOps tooling and open standards.
• Also responsible for other Duties/Projects as assigned by business management as needed.

Education and Work Experience:

• Bachelor's Degree Computer Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Required)
• Master's/Advanced Degree Computer Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Preferred)
• Data Engineering, Data Science (Required)
• Experience with big data architecture and pipeline, Spark (Required)
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and find opportunities for improvement Required
• Experience in programming languages such as Python/R, Java/Scala, and/ or Go Required(Required)
• Experience in Apache Spark and Databricks (Preferred)
• Experience in the telecom industry (Preferred)

Knowledge, Skills and Abilities:

• Experience with Python-based ML tooling including DSPy, LangGraph, and MLflow. Strong SQL skills for interacting with PostgreSQL and data lakes. (Required)
• Proficiency with distributed computing (Apache Spark, MosaicML), orchestration (MLflow), and graph-based AI workflows (LangGraph). (Required)

Licenses and Certifications:

• Databricks Certified Machine Learning Professional. (Preferred)
• Azure Machine Learning Engineer Associate or related cloud/AI certification. (Preferred)

#LI-Corporate

#LI-Hybrid

• At least 18 years of age
• Legally authorized to work in the United States

Base Pay Range: $97,700 - $176,200

Corporate Bonus Target: 15%

The pay range above is the general base pay range for a successful candidate in the role. The successful candidate's actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.

At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic sales incentive or bonus, based on their role. Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance and which is set at a percentage of the employee's eligible earnings in the prior year. Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance. To find the pay range for this role based on hiring location, ;paradox=1

At T-Mobile, our benefits exemplify the spirit of One Team, Together! A big part of how we care for one another is working to ensure our benefits evolve to meet the needs of our team members. Full and part-time employees have access to the same benefits when eligible. We cover all of the bases, offering medical, dental and vision insurance, a flexible spending account, 401(k), employee stock grants, employee stock purchase plan, paid time off and up to 12 paid holidays - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - paid parental and family leave, family building benefits, back-up care, enhanced family support, childcare subsidy, tuition assistance, college coaching, short- and long-term disability, voluntary AD&D coverage, voluntary accident coverage, voluntary life insurance, voluntary disability insurance, and voluntary long-term care insurance. We don't stop there - eligible employees can also receive mobile service & home internet discounts, pet insurance, and access to commuter and transit programs! To learn about T-Mobile's amazing benefits, check out ;br>
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As part of the T-Mobile team, you know the Un-carrier doesn't have a corporate ladder-it's more like a jungle gym of possibilities! We love helping our employees grow in their careers, because it's that shared drive to aim high that drives our business and our culture forward. By applying for this career opportunity, you're living our values while investing in your career growth-and we applaud it. You're unstoppable!

T-Mobile USA, Inc. is an Equal Opportunity Employer. All decisions concerning the employment relationship will be made without regard to age, race, ethnicity, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, religious affiliation, marital status, citizenship status, veteran status, the presence of any physical or mental disability, or any other status or characteristic protected by federal, state, or local law. Discrimination, retaliation or harassment based upon any of these factors is wholly inconsistent with how we do business and will not be tolerated.

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