AI​/ML Engineer​/Gen AI Engineer

Talent Acquisition Specialist

Location
:
Remote

Position Overview

The candidate will be responsible for designing, developing, and deploying machine learning models and AI-driven solutions to support healthcare analytics, improve operational efficiency, and drive business insights. This role requires strong expertise in machine learning, data engineering, cloud platforms, and end-to-end model lifecycle management.

Key Responsibilities

• Develop and implement scalable machine learning models for predictive analytics, classification, NLP, and optimization use cases.
• Work closely with data engineers and analysts to gather requirements, understand business problems, and translate them into ML solutions.
• Perform data preprocessing, feature engineering, model tuning, and validation.
• Build reusable ML pipelines and automate workflows through MLOps frameworks.
• Deploy models into production using cloud-native services (Azure, AWS, or GCP).
• Monitor and optimize model performance and ensure long-term model stability.
• Collaborate cross-functionally with product, engineering, and business stakeholders within Optum.
• Document solution designs, model behavior, and deployment architecture.

Mandatory Skills

• Strong programming skills in Python (Num Py, Pandas, Scikit-learn, Tensor Flow / PyTorch).
• Experience building ML models end-to-end, including training, validation, deployment, and monitoring.
• Hands‑on experience with NLP, LLMs, or generative AI technologies (Hugging Face, Lang Chain preferred).
• Knowledge of cloud platforms such as Azure, AWS, or GCP (Optum widely uses Azure & GCP).
• Familiarity with MLOps tools such as MLflow, Kubeflow, Vertex AI, Sage Maker, or Azure ML Studio.

Seniority level

Mid-Senior level

Employment type

Contract

Job function

Information Technology

Industries

Software Development