Sr Engineer, Machine Learning Engineering

Why this role

Derived from job-description analysis by Serendipath's career intelligence engine.

Skills & requirements

About the role

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 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, they ensure 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 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)
• 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:

Travel Required (Yes/No): No

DOT Regulated:

DOT Regulated Position (Yes/No): No

Safety Sensitive Position (Yes/No): No

Compensation Range:

Bellevue, WA: $165,100 to $223,300

Atlanta, GA: $143,900 to $194,700

Overland Part, KS: $138,300 to $187,100

Hern

Source: T-Mobile careers (LinkedIn)