Design, develop, fine-tune, and evaluate machine learning, deep learning, and Generative AI models.
Optimize model performance across accuracy, latency, scalability, and cost dimensions.
Design and implement scalable, production-ready AI solutions.
Build, maintain, and improve MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
Partner with Product Managers, Product Owners, Software Engineers, Data Scientists, and Research teams to align AI solutions with business and product objectives.
Work with structured and unstructured datasets, including healthcare, claims, and life sciences data, to build high-performance AI systems.

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
Minimum 3+ years of hands-on experience in an AI/ML or data science role delivering production-deployed solutions.
Strong proficiency in Python and SQL; experience building scalable ML/NLP workflows.
Deep hands-on experience with machine learning, deep learning, and natural language processing.
Experience working with Generative AI and Large Language Models, including fine-tuning and evaluation techniques.
Working knowledge of data preprocessing, feature engineering, and model validation practices.
Experience deploying AI solutions in cloud environments (Azure, AWS, or GCP).
Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).

AI/ML Engineer II

Key skills