Senior Engineer, Machine Learning Engineering

T-Mobile

Senior Engineer developing scalable AI solutions using large language models at T-Mobile. Collaborating with cross-functional teams to drive innovation in machine learning and generative AI technologies.

Posted 5/15/2026full-timeBellevue • Kansas, Virginia, Washington • 🇺🇸 United StatesSenior💰 $127,000 - $229,100 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudGoGoogle Cloud PlatformJavaPythonPyTorchScalaTensorflow

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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

Benefits

Comp & perks

medical, dental and vision insurance
flexible spending account
401(k)
employee stock grants
employee stock purchase plan
paid time off
up to 12 paid holidays
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
voluntary long-term care insurance
mobile service & home internet discounts
pet insurance
access to commuter and transit programs

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learninggenerative AIlarge language models (LLMs)MLOpsdata ingestionmodel deploymentmodel monitoringPythonRPyTorch

Soft Skills

collaborationmentoringcommunicationproblem-solvinginnovation

Certifications

Bachelor's Degree in Computer ScienceBachelor's Degree in Data ScienceBachelor's Degree in StatisticsBachelor's Degree in InformaticsBachelor's Degree in Information SystemsBachelor's Degree in Machine Learning