AI/ML Engineer

Job Description 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. AI/ML Engineers code and develop software that deploys ML models and algorithms into production. Communicate and present complex analytics results and concepts to leadership and internal stakeholders. Employ AI and/or ML that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR).Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. May adapt machine learning to areas such as artificial intelligence, robotics and other products that allow users to have an interactive experience. Work with large scale computing frameworks, data analysis systems. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory and machine learning using code for tool building, statistical analysis, using both general purpose software and statistical languages. Primary Responsibilities: - Contributes to the development, testing, deployment, and maintenance of machine learning models and AI-powered systems for Identity matching and mastering platform - Participate actively in the full AI lifecycle: contributing to brainstorming and conceptualization, rapid prototyping and experimentation, and writing high-quality, robust production code - Collaborate with stakeholders to preprocess, analyze, and interpret extensive datasets - Assist with the implementation and management of cloud infrastructure for AI solutions, learning and applying Infrastructure as Code principle - Utilize and contribute to reusable AI/ML platforms, components, and frameworks, helping to improve engineering efficiency - Actively seek guidance and learn from senior engineers through code reviews, pair programming, and technical discussions - Collaborate closely with product managers, designers, and other engineers to understand requirements, refine technical approaches, and deliver scalable, impactful AI solutions - Stay current with the latest advancements in AI/ML and software engineering, evaluate new technologies, and propose innovative ways to tackle healthcare challenges - Troubleshoot complex technical issues, identify root causes, and implement effective solutions in both development and production environments - Contribute to a team culture focused on technical excellence, continuous learning, and curiosity - Analyzes and investigates - 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: - Full time graduation degree - 4+ years of professional software engineering experience with a significant focus on building and deploying production-grade AI/ML models and systems - 4+ years of AI/ML Expertise: Understanding of core AI and machine learning concepts, models, and algorithms, demonstrated through practical application and system design. Ability to explain complex ideas clearly - LLM Experience: Hands-on experience building applications leveraging LLMs and deploying them into a production environment (considering aspects like performance, cost, reliability, monitoring). Good Understanding of Agentic AI, LangGraph, LangChain, RAG, Transformers - Broaden ML Domain Knowledge: Practical experience or solid knowledge in various machine learning domains such as Natural Language Processing (NLP), Computer Vision, Personalization & Recommendation systems, and/or Anomaly Detection - Solid Engineering Fundamentals: Proven growth in software design, data structures, algorithms, and writing clean, testable, and maintainable code - Solid programming skills in Python - Technical Breadth: Familiarity and hands-on experience with relevant technologies such as backend services ( Java), cloud platforms (AWS/Azure), front-end frameworks (React), CI/CD pipelines, REST/WebSocket API development, and database technologies Preferred Qualifications: - Certifications in AI/ML - Experience in Health Care Industry - Experience in Master Data Management or Record Linkage domain - Experience of AI/ML review process, UAIS and MLRB for internal employees - Experience on Apache Spark