Sr Engineer, Machine Learning Engineering

Compensation and Benefits

Base Pay Range: $127,000 – $229,100

Corporate Bonus Target: 15%

Location

United States – Georgia – Atlanta

Job Overview

The Senior Engineer, Machine Learning plays a pivotal role in advancing AI capabilities, focusing on the design, development, and deployment of large language models (LLMs) and generative AI solutions. This position is essential for building scalable, production‑grade AI systems that enable automation, personalization, and intelligent decision‑making across the enterprise. The role emphasizes the creation of innovative GenAI applications that deliver real‑world business impact while maintaining high standards of performance, reliability, and responsible AI practices. Collaborating with cross‑functional technical teams, the engineer ensures the seamless integration of LLM‑powered solutions into products and workflows, reinforcing the organization’s leadership in applying advanced AI technologies.

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 the same fields (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). At least 18 years of age. Legally authorized to work in the United States. Travel and Other Requirements

Travel Required: No

DOT Regulated Position: No

Safety Sensitive Position: No

Benefits

Life insurance, vision insurance, flexible benefit account, paid time off, paid holidays, tuition assistance, 401(k). Additional benefits include medical, dental, and vision insurance, a flexible spending account, employee stock grants, employee stock purchase plan, free money coaching, volunteer insurance options, and various family and childcare supports. Eligible employees can also receive mobile service & home internet discounts, commuter and transit programs, and pet insurance.

EEO Statement

T-Mobile USA, Inc. is an Equal Opportunity Employer. All decisions concerning the employment rel