Sr Engineer, Machine Learning Engineering

T-Mobile • Bellevue, WA

37d

About The Position

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.

Requirements

• 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)
• At least 18 years of age
• Legally authorized to work in the United States

Nice To Haves

• Master's/Advanced Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Preferred)
• Experience implementing fine-tuning, evaluation, and benchmarking techniques for LLMs and generative AI applications (Preferred)
• Experience in the telecom or large-scale enterprise domain (Preferred)
• 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)

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.

Benefits

• 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.
• 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.
• 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 account, 401(k), employee stock grants, employee stock purchase plan, paid time off and up to 12 paid holidays - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - 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, and voluntary long-term care insurance.
• eligible employees can also receive mobile service & home internet discounts, pet insurance, and access to commuter and transit programs!

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Telecommunications
• Number of Employees: 5,001-10,000 employees