Join OptumAI as a Senior Applied Scientist and drive the future of AI/ML in healthcare. This role offers a unique opportunity to contribute to groundbreaking inventions that enhance Optum's machine learning products and positively impact the healthcare business. As a key member of our team, you will set the standard for scientific excellence, influence technical decisions, and develop exemplary code, designs, and documentation that serve as organizational benchmarks.

This is a hands-on position for an AI/ML expert ready to tackle challenging problems, acquire new expertise, and translate complex issues into elegant, straightforward solutions. You will actively contribute design ideas and participate in constructive discussions regarding models and algorithms tailored for business needs.

Key responsibilities include leading the design and development of next-generation NLP, ML, and AI products and services specifically for the healthcare sector. You will build sophisticated machine learning and deep learning models, focusing on areas like NLP, NLU, NLG, and multidimensional time series forecasting. Expertise in RAG, LangChain, and VectorDBs is essential. A crucial part of the role involves quantizing and optimizing Generative AI models, managing the entire lifecycle of NLP and ML models for various products, and executing large-scale proof-of-concept projects for the healthcare business.

You will also manage prioritization and technology roadmaps for building comprehensive NLP, ML, and AI solutions. The role demands leading the complete end-to-end machine learning development process, from data ingestion and preparation to feature engineering, analysis, modeling, deployment, performance tracking, and documentation. Establishing best practices for deep learning and machine learning development cycles is vital to ensure process rigor and quality outcomes. Working with considerable autonomy to solve complex problems is expected. Collaboration with research, engineering, and product teams to translate AI advancements into production capabilities, while upholding ethical AI principles such as fairness, transparency, and accountability, is also paramount.

Required qualifications include a Master's degree in computer science with at least 4 years of industry experience, or a PhD with 2+ years of industry experience in data science, machine learning, or a related quantitative field. You should possess over 4 years of experience with Deep Learning Frameworks and distributed training, alongside 3+ years of experience in Machine Learning and Deep Learning modeling. A minimum of 2 years of experience applying computational algorithms and statistical methods to both structured and unstructured data is necessary. Furthermore, 1+ years of experience in GenAI model optimization and 1+ years of experience in Agentic AI are required. Proficiency in Statistics, Electrical/Electronic Engineering, or another quantitative discipline, coupled with proven excellent communication, writing, and presentation skills, is essential.

Preferred qualifications include experience mentoring and training scientists on complex technical issues and prior experience in the healthcare industry. Significant experience in deploying scalable solutions to complex problems, from initial problem definition through implementation and successful product launch, is highly desirable.