Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand, popular AI role title, and metro location create high candidate competition.
ML, LLM and MLOps expertise is domain-specific but moderately transferable across industries.
Requires production ML/LLM, cloud, MLOps, and deployment experience, enforcing strict technical filters.
Design, develop, and implement AI and Generative AI solutions using LLMs, Agentic AI frameworks, RAG architectures, and cloud AI platforms.
Develop and maintain scalable AI/ML pipelines, data workflows, and cloud integrations using platforms like Azure, Databricks, and AWS.
Implement Responsible AI and governance practices including bias detection, hallucination mitigation, explainability, and compliance with data ethics standards.
Bachelor's degree in Computer Science, Data Science, AI/ML, or related technical field.
Hands-on experience in developing and deploying production-level AI applications.
Experience with Python, Spark or SQL, and familiarity with at least one cloud platform (Azure, AWS, Databricks) and containerization technologies (Docker or Kubernetes).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in integrating AI capabilities with APIs, databases, and cloud services following MLOps and LLMOps best practices.
Familiar with AI/ML frameworks, vector databases, and orchestration frameworks like LangChain or similar technologies.
Capable of applying AI governance and Responsible AI principles to promote transparency, fairness, and safety in AI deployments.