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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Engineers, Machine Learning - **Company:** T-Mobile Us, Inc. - **Location:** Frisco, TX, United States (Remote available) - **Experience:** Expert - **Salary:** $146,700.0 - $156,700.0 - **Contract:** Permanent contract - **Skills:** LTE (Telecommunication), Amazon Web Services, Automated Storage and Retrieval Systems, Microsoft Azure, Cloud Engineering, Information Systems, Databases, Continuous Integration, Graph Database, Information Retrieval, Python (Programming Language), Machine Learning, Named Entity Recognition, Open Source Technology, Software Product Management, Azure Machine Learning, Search Technologies, Software Deployment, SQL Databases, Enterprise Software Applications, Feature Engineering, Data Ingestion, Transfer Learning, Large Language Models, Prompt Engineering, Generative AI, Information Technology, HuggingFace, Machine Learning Operations, Virtual Agents, Document Classification, Oracle Cloud Infrastructure, Docker - **Published:** September 4, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/88241931/1 ## About the Role * Experience (1) Experience developing and deploying enterprise-scale applications powered by Large Language Models, including API integration with LLM providers (including OpenAI, Anthropic, Azure OpenAI, or open-source models via Hugging Face), prompt engineering, and response handling for production user-facing systems. * Experience (2) Experience implementing Retrieval-Augmented Generation (RAG) architectures in LLM applications, including document ingestion pipelines, embedding generation, vector database integration, and semantic retrieval systems for knowledge-based applications. * Experience (3) Experience designing and deploying NLP and semantic understanding systems including Named Entity Recognition (NER), text classification, semantic search, and entity disambiguation on cloud platforms (AWS, OCI, or Azure). * Experience (4) Experience establishing MLOps/AIOps practices for production machine learning systems, including containerized model serving infrastructure using Docker and Kubernetes for LLM inference at scale, model optimization techniques (quantization, distillation, or runtime optimization), observability instrumentation, and CI/CD pipeline implementation. * Experience (5) Experience fine-tuning Large Language Models using transfer learning, few-shot learning, or prompt engineering techniques for domain-specific applications and custom use cases. * Experience (6) Experience designing and implementing knowledge graph architectures or structured knowledge bases integrated with Large Language Models for enhanced reasoning, entity disambiguation, and information retrieval in enterprise applications. Experience and education requirements: PRIMARY REQUIREMENTS: Master's degree in Computer Science, Statistics, Informatics, Information Systems, Machine Learning, or related, and 3 years of relevant work experience. ALTERNATIVE REQUIREMENTS: Bachelor's degree in Computer Science, Statistics, Informatics, Information Systems, Machine Learning, or related, and 5 years of relevant work experience. Telecommuting is permitted, but applicant must work from the worksite location at least 3-4 days per week. No additional national or international travel is anticipated. ## Description T-Mobile is America's supercharged Un-carrier, delivering an advanced 4G LTE and transformative nationwide 5G network that will offer reliable connectivity for all. Sr Engineers, Machine Learning located in Frisco, Texas will enable systems for coding, deploying, and maintaining large-scale machine learning models throughout their lifecycle., * Lead the architecture, design, and development of enterprise-scale machine learning and Generative AI systems, ensuring alignment with T-Mobile's strategic business objectives. * Architect end-to-end ML pipelines including data ingestion, feature engineering, model training, optimization, and deployment using Python, SQL, and cloud-native ML services such as AWS SageMaker or Amazon Bedrock. * Design and implement production AI systems on cloud platforms (AWS, GCP, or Azure), making strategic technology selections for compute, storage, and inference infrastructure. * Develop and deploy autonomous AI agent architectures with Retrieval-Augmented Generation (RAG) capabilities for conversational AI, intelligent assistants, and enterprise task-automation applications. * Establish and drive organization-wide standards for MLOps practices including CI/CD pipelines, model versioning, monitoring, and governance to ensure production reliability and compliance. * Evaluate emerging Generative AI technologies, benchmark large language models, and provide technical recommendations that influence T-Mobile's AI product roadmap. * Translate complex machine learning concepts and model behaviors into actionable insights for executive leadership and cross-functional business stakeholders. * Mentor and provide technical leadership to teams of data scientists and ML engineers, fostering best practices in GenAI development and production deployment. * Collaborate with industry partners, cloud providers, and research communities to identify and adopt cutting-edge AI advancements. * Drive the successful delivery of advanced GenAI solutions including large language model applications, conversational AI systems, and intelligent automation platforms. ## Related Videos - [Unlocking the Power of AI: Accessible Language Model Tuning for All](https://www.wearedevelopers.com/videos/951-unlocking-the-power-of-ai-accessible-language-model-tuning-for-all) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Adding knowledge to open-source LLMs](https://www.wearedevelopers.com/videos/1522-adding-knowledge-to-open-source-llms) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The Best Large Language Models on The Market](https://www.wearedevelopers.com/magazine/319-the-best-large-language-models-on-the-market)