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Mid-level popular ML role across multiple Indian metros with a 5+ years requirement increases applicant density.
Technical ML/GenAI skills transfer across industries, but Azure/Databricks and regulated-domain experience increase domain specificity.
Explicit 5+ years, mandatory Databricks/Azure/LLM production experience and specific tech stack create strict filters.
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Lead end-to-end machine learning projects including design, implementation, deployment, and monitoring of models across ML, deep learning, NLP, and GenAI domains.
Collaborate with business, engineering, and product teams to translate complex problems into scalable production-grade solutions on Azure infrastructure.
Mentor junior data scientists and establish standards for responsible AI, code quality, experimentation, and model evaluation.
Advanced degree (MS or PhD) in computer science, statistics, mathematics, analytics, or related quantitative field.
5+ years of applied machine learning experience with production model delivery.
Strong Python skills with experience in scikit-learn, PyTorch or TensorFlow, Hugging Face Transformers, and Databricks (MLflow, PySpark).
Experience deploying and maintaining ML models in production on Azure platforms, including Azure AI Foundry and Azure OpenAI service.
Experienced practitioner with broad expertise across traditional ML, deep learning, NLP, and LLM/GenAI applications including prompt engineering and retrieval-augmented generation.
Comfortable working with large-scale data pipelines and production MLOps practices including CI/CD, model versioning, drift detection.
Able to engage and communicate complex technical concepts effectively with senior leadership, clients, and cross-functional teams.