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Engineer, Machine Learning Engineer

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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!

Job Overview
The Machine Learning (ML) Engineer plays a pivotal role in advancing AI capabilities, focusing on the design, development, and deployment of machine learning models with an emphasis on large language models (LLMs) and state-of-the-art technologies. This position is essential for building scalable AI applications that deliver real-world impact, ensuring models are optimized for performance, reliability, and responsible use. Collaborating with various technical teams, they facilitate the seamless integration of LLM-powered applications into products and workflows. Their expertise ensures the organization remains at the forefront of AI innovation, reinforcing a culture of continuous improvement and leadership in applying advanced AI technologies.

Job Responsibilities:

  • Build and maintain the entire machine learning lifecycle (research, design, experimentation, development, deployment, monitoring, and maintenance).  

  • Assemble large, complex data sets that meet functional/ non-functional business requirements for machine learning.  

  • Collaborate with data science, tech, and product teams on defining, architecting, and building data ingestion systems and model training pipelines from experimentation to deployment, monitoring, and continuous performance improvement.  

  • Design, develop, and deploy machine learning and large language models (LLMs) to power scalable AI applications. 

  • Fine-tune, optimize, and maintain AI models to ensure performance, reliability, and responsible use. 

  • Collaborate with cross-functional technical teams to integrate AI-driven solutions into products, platforms, and workflows. 

  • Conduct rigorous evaluations and benchmarking of AI models and applications to validate accuracy, efficiency, and trustworthiness. 

  • Research and apply emerging machine learning techniques and AI frameworks to advance innovation and maintain industry leadership. 

  • Build and maintain pipelines, tooling, and infrastructure for model training, deployment, and monitoring in production environments. 

  • Ensure scalability, security, and compliance of AI systems while aligning with business and operational requirements. 

  • Participate in other duties or projects as assigned by business management as needed. 

Education:

  • Bachelor's Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Required)  

  • Master's/Advanced Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Preferred)  


 
Work Experience: 

  • Data Engineering, Data Science (Required)  

  • Experience designing, developing, and deploying machine learning models and large language models (LLMs) in production environments (Required) 

  • Experience building and maintaining end-to-end ML pipelines including data ingestion, training, deployment, monitoring, and optimization (Required) 

  • Experience applying MLOps practices and cloud platforms (AWS, GCP, or Azure) for scalable AI solutions (Preferred) 

  • Experience implementing fine-tuning, evaluation, and benchmarking techniques for LLMs and generative AI applications (Preferred) Experience collaborating with cross-functional teams (engineering, data science, and product) to deliver AI-powered applications (Required)Experience in programming languages such as Python/R, Java/Scala, and/ or Go (Required)  

  • Experience in the telecom industry (Preferred)  

Knowledge, Skills and Abilities:

  • Proficiency in building and deploying machine learning models and algorithms (Required) 

  • Ability to identify, troubleshoot, and resolve complex technical issues (Required) 

  • Strong analytical and problem-solving abilities with attention to model performance, fairness, and responsible AI practices (Preferred) 

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

    Travel:
    Travel Required (Yes/No): No

    DOT Regulated:
    DOT Regulated Position (Yes/No): No
    Safety Sensitive Position (Yes/No): No

    Base Pay Range: $104,800 - $189,100

    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, click here.

    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 www.t-mobilebenefits.com.

    Never stop growing!
    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.

    Talent comes in all forms at the Un-carrier. If you are an individual with a disability and need reasonable accommodation at any point in the application or interview process, please let us know by emailing ApplicantAccommodation@t-mobile.com or calling 1-844-873-9500. Please note, this contact channel is not a means to apply for or inquire about a position and we are unable to respond to non-accommodation related requests.

    T-Mobile maintains a drug-free workplace.