Associate AI/ML Engineer

Optum is hiring an Associate AI/ML Engineer for its Hyderabad team. The role involves designing, developing, testing, and deploying AI/ML solutions using Python and modern machine learning frameworks.

The role focuses on data preparation, exploratory data analysis, feature engineering, model development, validation, deployment, monitoring, and continuous improvement. The engineer will collaborate with data engineers, data scientists, and cross-functional teams to build scalable AI-enabled applications and production-grade ML systems.

Key Responsibilities

• Assist in designing, developing, testing, and deploying AI/ML solutions.
• Perform data preparation, exploratory data analysis, and feature engineering.
• Develop and maintain machine learning models.
• Train and validate ML models using modern frameworks.
• Collaborate with data engineers and data scientists to build scalable data pipelines.
• Monitor model performance and conduct drift analysis.
• Support ML workflows, experiment tracking, and model documentation.
• Translate business requirements into AI/ML solutions.
• Contribute to Responsible AI practices including fairness, reliability, explainability, and data privacy.
• Create and maintain technical documentation and project artifacts.
• Support scalable ML infrastructure and production deployments.
• Contribute to observability, automation, security, and operational excellence.
• Collaborate with front-end teams when required for ML product integration.
• Stay current with emerging AI/ML tools, frameworks, and research.

Required Skills

• Artificial Intelligence
• Machine Learning
• Python
• SQL
• Pandas
• NumPy
• Scikit-Learn
• TensorFlow
• PyTorch
• Data Preparation
• Exploratory Data Analysis (EDA)
• Feature Engineering
• Model Development
• Model Training
• Model Evaluation
• Model Validation
• Model Deployment
• Model Selection
• Model Optimization
• Model Tuning
• ML Workflows
• ML Pipelines
• Experiment Tracking
• Model Monitoring
• Drift Analysis
• ML Observability
• Production ML
• ML Infrastructure
• Cloud Computing
• Azure
• GCP
• Data Engineering
• Real-Time Data Pipelines
• Batch Data Pipelines
• Distributed Data Processing
• Business Requirements Analysis
• Technical Problem Solving
• Responsible AI
• Data Privacy
• Scalability
• Security
• Reliability
• Automation
• Technical Documentation

Additional / Preferred Skills

• AWS
• MLflow
• Feature Stores
• ONNX
• Vector Databases
• Synapse
• BigQuery
• Dataflow
• Databricks
• Kafka
• EventHub
• Pub/Sub
• Architecture Diagrams
• C4 Models
• ADRs
• Technical Specifications
• Cloud-Native ML Deployment
• Front-End Integration
• UX Collaboration