At T-Mobile, the business problem is to advance AI capabilities by designing, developing, and deploying machine learning models with an emphasis on large language models (LLMs) and state-of-the-art technologies to deliver real-world impact.
Requirements
- 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)
- Proficiency in building and deploying machine learning models and algorithms (Required)
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.
Other
- 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)
- At least 18 years of age
- Legally authorized to work in the United States
- Travel Required (Yes/No): No
