Join Optum, a global leader dedicated to improving health outcomes through innovative technology. As an AI/ML Engineer specializing in NLP and Generative AI, you will be instrumental in developing and deploying cutting-edge solutions. Our inclusive culture, talented colleagues, and commitment to career development offer a unique environment to make a significant impact.

Advance global health optimization by connecting people with the care, pharmacy benefits, data, and resources they need. Embrace our mission of Caring. Connecting. Growing together. This role offers a chance to innovate and contribute to a healthier future for millions.

Design, develop, and deploy advanced AI and Machine Learning solutions, focusing on NLP, LLMs, and RAG. Optimize AI models for performance, scalability, and maintainability. Evaluate emerging AI technologies and translate business needs into measurable AI-driven outcomes.

Collaborate with data engineering for robust data pipelines and work with diverse data types to enhance model accuracy. Implement MLOps best practices for seamless production deployment and lifecycle management. Ensure AI solutions are secure, scalable, and operationally efficient.

Apply Responsible AI principles, monitor model performance, and manage operational risks. Partner with cross-functional teams to define and deliver AI solutions. Mentor engineers, promote engineering excellence, and communicate technical concepts effectively to all stakeholders.

A Bachelor's or Master's degree in Computer Science, AI, ML, Data Science, or a related engineering field is required, coupled with over 5 years of professional experience in developing and deploying AI/ML solutions. Proven experience building and deploying machine learning models into production environments is essential.

Proficiency in Python and experience with AI/ML frameworks like TensorFlow, PyTorch, Scikit-learn, LangChain, or similar technologies are critical. Familiarity with APIs, microservices, cloud-native applications, and Agile methodologies is expected. A strong understanding of supervised/unsupervised learning, deep learning, NLP, LLMs, feature engineering, and model evaluation techniques is necessary.

Excellent analytical, problem-solving, communication, and stakeholder management skills are vital. The ability to work independently while effectively collaborating across teams is a key requirement. Experience with CI/CD, software testing, observability, and secure development practices is also expected.