• Develop and deploy machine learning, deep learning, NLP, and Generative AI models for enterprise-level healthcare applications.
• Build scalable AI pipelines, integrate models into production systems, and optimize performance.
• Work closely with cross-functional teams — including engineering, product, and data teams — to develop AI-driven features and solutions.
• Conduct data analysis, feature engineering, and model evaluation using best practices.
• Research and implement state-of-the-art algorithms to improve automation, accuracy, and system intelligence.
• Lead technical discussions, mentor junior AI engineers, and contribute to architectural decisions.
• Ensure AI systems comply with security, privacy, and regulatory standards relevant to healthcare.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
• 3+ years of hands-on experience in AI/ML engineering, model development, and deployment.
• Strong proficiency in Python and frameworks such as TensorFlow, PyTorch, scikit-learn, and HuggingFace Transformers.
• Solid understanding of Generative AI, LLMs, vector databases, embeddings, and retrieval-augmented generation (RAG).
• Experience with MLOps tools, containerization (Docker), and cloud platforms (AWS, Azure, or GCP).
• Knowledge of data pipelines, ETL workflows, and APIs.
• Strong problem-solving, analytical, and communication skills.
• Ability to work independently and collaboratively in a fast-paced environment.

Tools / Skills