Required Qualifications :

- Master's or Relevant in Computer Science, Machine Learning, or related field

- 6+ years of experience in AIML engineering and research

- Hands-on experience with MLOps, model deployment, and monitoring

- Deep, hands-on experience with FastAPI and Pydantic for building robust, schema-validated microservices

- Experience with experiment tracking tools (e.g., Weights & Biases, MLflow)

- Experience building systems that communicate via message queues like Azure Service Bus

- Experience in explainable AI (AXI) tools - such as LIME and SHAP

- Cloud-Native Development : Solid experience with Docker for applications and deploying orchestrated environments like Kubernetes (AKS)

- In-depth knowledge of LLM vulnerabilities (OWASP Top 10 for LLMs) and experience implementing guardrails against prompt injections and data

- Familiarity with AIML governance, ethics, and responsible AI practices

- Proven expertise in LLMs, generative AI, and deep learning

- Solid programming skills in Python and familiarity with ML libraries (e.g., scikit-learn, Keras)

- Asynchronous & Concurrent Programming : Mastery of Python's asyncio to build scalable, I/O-bound services

- Expert-level Python for Production Systems : Proven ability to architect and write clean, typed, and testable code for distributed systems