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.
Primary Responsibilities:
- Design, develop, train, and evaluate machine learning, deep learning, and generative AI models to solve business problems
- Apply appropriate techniques such as classification, regression, clustering, dimensionality reduction, and feature engineering
- Build and optimize GenAI solutions, including prompt engineering, finetuning, model optimization, and inference performance improvements
- Run proofofconcepts and experiments, baseline results, and compare models against production or reference systems
- Partner with data engineering and business teams to understand the problem space and required datasets
- Prepare, clean, validate, and manage structured and unstructured data used for training and inference
- Identify and handle data quality issues such as imbalance, drift, missing values, and inconsistencies
- Ensure proper handling of sensitive data (PII/PHI) in accordance with governance and compliance standards
- Work with AI and data platforms such as Databricks, PySpark, and cloud services (Azure, AWS, GCP)
- Develop APIs and services (REST, FastAPI) to expose ML and GenAI capabilities to applications
- Containerize and deploy AI services using Docker and cloudnative services
- Utilize version control systems and follow engineering best practices including code reviews and pair programming
- 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 regard 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, Engineering, Data Science, or a related technical field
- Handson experience in applying machine learning, deep learning, and/or generative AI models in realworld or productionlike environments
- Experience applying statistical models, machine learning models, deep learning models, and generative AI models
- Experience with software engineering best practices, including version control (e.g., GitHub), code reviews, and collaborative development
- Experience with containerization technologies such as Docker
- Solid foundational understanding of machine learning concepts, including supervised and unsupervised learning
- Knowledge of common techniques such as classification, regression, clustering, dimensionality reduction, and feature engineering
- Proficiency in Python for data processing, model development, and AI application development
- Familiarity with building APIs (REST / FastAPI) and developing AIpowered services.
