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 diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start

Caring. Connecting. Growing together.

We are looking for a Data Scientist to drive end-to-end ML and DL projects.

Primary Responsibility :

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 of Technology

Knowledge of Large Language Models (LLMs) for text and conversational applications

Familiarity with data cleaning, feature engineering, and model evaluation best practices

Proficiency in Python, including libraries like pandas, NumPy, and scikit-learn

Demonstrated ability to build, train, and optimize machine learning models for production

Proven excellent analytical thinking and communication skills for cross-functional collaboration

Preferred Qualifications :

Hands-on experience with deep learning frameworks (TensorFlow / PyTorch)

Experience using cloud platforms (AWS / GCP / Azure) for scalable deployments

Exposure to Retrieval-Augmented Generation (RAG) methodologies and AI Agents