Washington Staffing
Sr Engineer, Machine Learning Engineering
Washington Staffing, Bellevue, Washington, us, 98009
Senior Engineer, Machine Learning
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 exp
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 exp