Senior AI or ML Engineer

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

This role involves collaborating with data engineers and data scientists to integrate generative AI solutions into our production environment. The ideal candidate will have a solid background in machine learning operations, software engineering, and a passion for building/deploying scalable AI solutions, including RAG and LLM-based systems.

Primary Responsibilities

• Design, develop, and implement MLOps pipelines for the continuous integration and deployment of generative AI models
• Collaborate with data engineers to ensure seamless data flow and integration for AI model training and deployment
• Work closely with data scientists to understand model requirements and optimize deployment processes
• Automate the training, testing, and deployment processes for generative AI models
• Monitor and maintain AI models in production, ensuring optimal performance, accuracy, and reliability
• Implement best practices for version control, model reproducibility, and governance
• Optimize machine learning pipelines for scalability, efficiency, and cost-effectiveness
• Troubleshoot and resolve issues related to model deployment and performance
• Ensure compliance with security and data privacy standards in all MLOps activities
• Stay up to date with the latest MLOps tools, technologies, and trends
• Provide support and guidance to other team members on MLOps practices
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
  
  

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field
• 15+ years of overall experience and 3-5 years of experience in MLOps, DevOps, or a related field
• Hands-on experience with automated testing and deployment of machine learning models
• Experience working in an Agile/Scrum development process
• Solid understanding of machine learning principles and model lifecycle management
• Proven excellent problem-solving skills and ability to troubleshoot complex issues
• Proven solid communication and collaboration skills
  
  

Technical Skills

• Programming Languages: Proficiency in Python, Scala, and SQL
• Machine Learning Frameworks: Experience with TensorFlow, PyTorch, and Scikit-learn
• Automation Tools: Proficiency with Jenkins, Git, and Docker
• Cloud Platforms: Experience with AWS, Azure, or Google Cloud and their respective machine learning services
• Containerization and Orchestration: Knowledge of Docker and Kubernetes
• Data Engineering Tools: Familiarity with Apache Spark, Kafka, and ETL processes
• Version Control: Proficiency in using Git
• Monitoring Tools: Experience with Prometheus, Grafana, or similar tools
• CI/CD Pipelines: Knowledge of CI/CD best practices and tools
• Security and Compliance: Understanding of security best practices and data privacy regulations
• RAG and ALLM Development: RAG Solutions: Experience in developing RAG solutions, including designing data pipelines for document ingestion, chunking, enrichment, embedding, and retrieval
• Familiarity with tools like LangChain and LlamaIndex for building RAG applications
• ALLM Solutions: Proficiency in integrating advanced large language models (ALLMs) into production environments
• Knowledge of optimizing LLMs for specific tasks, managing model lifecycle, and ensuring efficient resource utilization
  
  

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.