Back
Tier-1 brand, metro location, popular mid-level GenAI title, and broad required stack increases competition.
Specialized GenAI and ML tooling required, making the role moderately transferable across industries.
Explicit 4–7 years plus mandatory ML/GenAI, cloud, and tooling requirements indicate strict shortlisting filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and deploy scalable Generative AI solutions using LLMs and transformer architectures.
Build and optimize model workflows, including fine-tuning and prompt engineering, integrating AI capabilities into enterprise systems via APIs.
Collaborate with data engineers and MLOps teams to productionize models on cloud platforms (Azure/AWS/GCP) ensuring robustness, scalability, and compliance.
4 to 7 years of work experience in relevant fields.
Bachelor's degree in Technology (B.E/B.Tech) or equivalent (M.Tech/MCA also acceptable).
Proficient in Python, PyTorch, Hugging Face Transformers, Azure/AWS/GCP cloud platforms.
Experience with orchestration frameworks (LangChain or similar), REST API frameworks (FastAPI/Flask), and ML pipeline tools (MLflow, Weights & Biases).
Experienced in implementing and fine-tuning foundation models and managing ML workflows in enterprise cloud environments.
Skilled in AI model deployment and CI/CD practices specifically for ML products using Azure ML or SageMaker pipelines.
Comfortable working at the intersection of AI research, engineering, and operationalization with a focus on Generative AI and emerging technologies.