· 4–7 years of experience in AI/ML engineering or applied data science roles.
· Strong hands on experience with Python and ML libraries (e.g., scikit learn, PyTorch, TensorFlow).
· Experience building end to end ML solutions from data to deployment.
· Practical exposure to GenAI / LLM concepts (prompting, embeddings, RAG, APIs).
· Experience working in cloud environments (Azure preferred).
· Ability to communicate effectively with both technical and non technical stakeholders.
Preferred Qualifications:
· Experience in healthcare, insurance, or regulated industries.
· Familiarity with Azure ML, Databricks, or similar platforms.
· Exposure to agent based or workflow oriented AI systems.
· Consulting or client facing delivery experience.
· Knowledge of Responsible AI, model governance, or compliance workflows.