T-MOBILE USA, Inc.
Sr Engineer, Machine Learning Engineering
T-MOBILE USA, Inc., Factoria, Washington, United States
Job Overview
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 Responsibilities
Build and manage the complete machine‑learning and generative AI lifecycle, including research, design, experimentation, development, deployment, monitoring, and maintenance.
Design, develop, and deploy LLM‑based and generative AI models to power scalable and intelligent enterprise applications.
Architect, optimize, and maintain retrieval‑augmented generation (RAG), prompt orchestration, and contextual reasoning pipelines to support diverse AI use cases.
Implement scalable MLOps pipelines for model deployment, performance monitoring, and continuous improvement.
Conduct fine‑tuning, alignment, and evaluation of LLMs and multimodal models to ensure reliability, efficiency, and fairness.
Collaborate with data science, engineering, and product teams to translate business needs into generative AI‑driven solutions.
Perform benchmarking, evaluation, and optimization of generative models to improve accuracy, latency, and cost efficiency.
Research and apply emerging techniques in transformer architectures, multimodal learning, and generative modeling to drive innovation and enhance enterprise capabilities.
Ensure secure, ethical, and responsible AI deployment, embedding fairness, transparency, and compliance throughout the model lifecycle.
Mentor and guide team members on generative AI frameworks, best practices, and experimentation methodologies.
Participate in other duties or projects as assigned by business management as needed.
Education and Work Experience
Bachelor's Degree in Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Required).
Master's/Advanced Degree in Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Preferred).
1+ year of experience in designing, developing, and deploying large language models (LLMs) and generative AI systems in production environments (Required).
5+ years of experience building and maintaining end‑to‑end ML pipelines, including data ingestion, training, deployment, monitoring, and optimization (Required).
3+ years of experience applying MLOps practices and leveraging cloud platforms (AWS, GCP, or Azure) for scalable AI solutions (Required).
Experience implementing fine‑tuning, evaluation, and benchmarking techniques for LLMs and generative AI applications (Preferred).
5+ years of experience collaborating with cross‑functional teams (engineering, data science, and product) to deliver AI‑powered applications (Required).
2+ years of experience in programming languages such as Python/R, Java/Scala, and/or Go, with hands‑on experience in frameworks such as PyTorch, TensorFlow, LangChain, or Hugging Face (Required).
Experience in the telecom or large‑scale enterprise domain (Preferred).
Knowledge, Skills and Abilities
5+ years in designing, building, and deploying machine‑learning and generative AI models (Preferred).
5+ years of experience identifying, troubleshooting, and resolving complex technical and operational challenges (Preferred).
4+ years of strong analytical and problem‑solving abilities with attention to model performance, reliability, and responsible AI practices (Preferred).
2+ years of experience with transformer architectures, embeddings, and multimodal learning techniques (Preferred).
Other Requirements
At least 18 years of age.
Legally authorized to work in the United States.
Travel Travel Required:
No
Base Pay Range Base Pay Range: $127,000 – $229,100. Corporate Bonus Target: 15%.
Benefits At T-Mobile, our benefits exemplify the spirit of One Team, Together! Full and part‑time employees have access to medical, dental, and vision insurance; a flexible spending account; 401(k); employee stock grants; employee stock purchase plan; paid time off; 12 paid holidays for new full‑time employees; 2.5 paid holidays for new part‑time employees; paid parental and family leave; childcare subsidy; tuition assistance; and many other benefits. Eligible employees can also receive mobile service & home internet discounts, pet insurance, and access to commuter and transit programs.
EEO Statement 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.
Disability Accommodation If you have 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. 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.
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Job Responsibilities
Build and manage the complete machine‑learning and generative AI lifecycle, including research, design, experimentation, development, deployment, monitoring, and maintenance.
Design, develop, and deploy LLM‑based and generative AI models to power scalable and intelligent enterprise applications.
Architect, optimize, and maintain retrieval‑augmented generation (RAG), prompt orchestration, and contextual reasoning pipelines to support diverse AI use cases.
Implement scalable MLOps pipelines for model deployment, performance monitoring, and continuous improvement.
Conduct fine‑tuning, alignment, and evaluation of LLMs and multimodal models to ensure reliability, efficiency, and fairness.
Collaborate with data science, engineering, and product teams to translate business needs into generative AI‑driven solutions.
Perform benchmarking, evaluation, and optimization of generative models to improve accuracy, latency, and cost efficiency.
Research and apply emerging techniques in transformer architectures, multimodal learning, and generative modeling to drive innovation and enhance enterprise capabilities.
Ensure secure, ethical, and responsible AI deployment, embedding fairness, transparency, and compliance throughout the model lifecycle.
Mentor and guide team members on generative AI frameworks, best practices, and experimentation methodologies.
Participate in other duties or projects as assigned by business management as needed.
Education and Work Experience
Bachelor's Degree in Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Required).
Master's/Advanced Degree in Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Preferred).
1+ year of experience in designing, developing, and deploying large language models (LLMs) and generative AI systems in production environments (Required).
5+ years of experience building and maintaining end‑to‑end ML pipelines, including data ingestion, training, deployment, monitoring, and optimization (Required).
3+ years of experience applying MLOps practices and leveraging cloud platforms (AWS, GCP, or Azure) for scalable AI solutions (Required).
Experience implementing fine‑tuning, evaluation, and benchmarking techniques for LLMs and generative AI applications (Preferred).
5+ years of experience collaborating with cross‑functional teams (engineering, data science, and product) to deliver AI‑powered applications (Required).
2+ years of experience in programming languages such as Python/R, Java/Scala, and/or Go, with hands‑on experience in frameworks such as PyTorch, TensorFlow, LangChain, or Hugging Face (Required).
Experience in the telecom or large‑scale enterprise domain (Preferred).
Knowledge, Skills and Abilities
5+ years in designing, building, and deploying machine‑learning and generative AI models (Preferred).
5+ years of experience identifying, troubleshooting, and resolving complex technical and operational challenges (Preferred).
4+ years of strong analytical and problem‑solving abilities with attention to model performance, reliability, and responsible AI practices (Preferred).
2+ years of experience with transformer architectures, embeddings, and multimodal learning techniques (Preferred).
Other Requirements
At least 18 years of age.
Legally authorized to work in the United States.
Travel Travel Required:
No
Base Pay Range Base Pay Range: $127,000 – $229,100. Corporate Bonus Target: 15%.
Benefits At T-Mobile, our benefits exemplify the spirit of One Team, Together! Full and part‑time employees have access to medical, dental, and vision insurance; a flexible spending account; 401(k); employee stock grants; employee stock purchase plan; paid time off; 12 paid holidays for new full‑time employees; 2.5 paid holidays for new part‑time employees; paid parental and family leave; childcare subsidy; tuition assistance; and many other benefits. Eligible employees can also receive mobile service & home internet discounts, pet insurance, and access to commuter and transit programs.
EEO Statement 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.
Disability Accommodation If you have 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. 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.
#J-18808-Ljbffr