Sr Engineer, Machine Learning Engineering

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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

Base Pay Range: $127,000 - $229,100

Corporate Bonus Target: 15%

The pay range above is the general base pay range for a successful candidate in the role. The successful candidate's actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.

At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic sales incentive or bonus, based on their role. Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance and which is set at a percentage of the employee's eligible earnings in the prior year. Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance. To find the pay range for this role based on hiring location, copy and paste this link into your browser:

At T-Mobile, our benefits exemplify the spirit of One Team, Together A big part of how we care for one another is working to ensure our benefits evolve to meet the needs of our team members. Full and part-time employees have access to the same benefits when eligible. We cover all of the bases, offering medical, dental and vision insurance, a flexible spending