AI/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. The AI/ML Engineer (SG27) will design, develop, and operationalize AI/ML, Generative AI, LLM, and Agentic AI solutions that drive intelligent automation and business value. The role requires strong expertise in PySpark, Scala Spark, Azure Cloud, and modern AI/ML technologies to build scalable batch, streaming, and cloud-native data platforms. The engineer will collaborate with data science, architecture, and business teams to deliver enterprise AI solutions, implement MLOps best practices, and ensure the reliability, scalability, and governance of AI applications. Additionally, they will contribute to AI strategy, data platform architecture, automation frameworks, and continuous innovation across the enterprise data ecosystem.

Partner with Data Science and AI/ML teams to design, develop, and deploy machine learning, Generative AI, and Agentic AI solutions that drive predictive analytics, automation, and business value Build and operationalize LLM-powered applications, including RAG frameworks, AI agents, prompt engineering, orchestration workflows, and contextual data enrichment Deploy, monitor, and govern AI/ML models using Azure ML, Databricks ML, Azure AI Search, and modern MLOps practices Integrate AI/ML and LLM capabilities into enterprise data platforms, ensuring scalability, security, compliance, and responsible AI practices Design and develop scalable AI-enabled data pipelines using PySpark, Scala Spark, and Azure Cloud technologies Collaborate with architecture, data engineering, and business teams to translate business requirements into production-ready AI solutions Develop and optimize RAG, vector search, semantic retrieval, and knowledge management frameworks for enterprise AI applications Build and maintain batch, streaming, and real-time AI data processing pipelines leveraging Azure Event Hub and Spark Structured Streaming Implement CI/CD and MLOps automation using GitHub Actions, Jenkins, Docker, Kubernetes, and Azure DevOps Evaluate emerging AI technologies, frameworks, and tools to drive innovation and continuous improvement Develop prototypes, proof-of-concepts (POCs), and production-grade AI applications while participating in architecture, design, and code reviews Create technical documentation and provide support for AI/ML application deployments, monitoring, and incident resolution 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 or Master's degree in Computer Science, Information Technology, or equivalent 5+ years of professional experience in AI/ML engineering, including machine learning, Generative AI, LLM-based applications, Agentic AI frameworks, and Big data platform development Solid hands-on experience with Python and Scala Experience building large-scale batch and streaming data processing systems Proven experience