- Develop and deploy machine learning models and AI solutions for healthcare use cases.

- Build and maintain end-to-end ML pipelines (data preparation, feature engineering, model training, evaluation, and deployment).

- Work with healthcare data such as EHR/EMR, claims, and clinical text to generate insights and support analytics solutions.

- Apply AI/ML techniques including NLP, deep learning, and predictive modeling to solve business and clinical problems.

- Collaborate with cross-functional teams to translate requirements into scalable AI-driven solutions.

- Communicate model outcomes and analytical insights to stakeholders in a clear and structured manner.

- Adhere to engineering standards, MLOps practices, and healthcare compliance requirements (e.g., HIPAA).

- Graduate degree or equivalent experience.

- Bachelor degree in Computer Science, AI/ML, Data Science, Statistics, or related field.

- 2-5 years of experience in machine learning, AI development, or data-driven engineering roles.

- Proficiency in Python and experience with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.

- Strong understanding of machine learning fundamentals, statistics, and data modeling concepts.

- Experience with data tools such as Pandas, NumPy, and SQL.