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Tier-1 employer, mid-level GenAI role in Bangalore with broad skillset attracts high competition.
Specialized LLM, PyTorch, and MLOps skills make transfers across industries challenging, indicating high sensitivity.
Explicit 4–7 years and mandatory PyTorch, Transformers, LangChain, cloud and MLOps imply high shortlisting strictness.
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Design, develop, and deploy scalable Generative AI solutions using large language models (LLMs) and transformer architectures.
Build and optimize model pipelines with frameworks like PyTorch, Hugging Face Transformers, and LangChain, including fine-tuning with domain-specific data.
Collaborate with data engineers and MLOps teams to productionize GenAI models on cloud platforms (Azure, AWS, GCP) ensuring robustness, scalability, and enterprise integration via APIs.
4 to 7 years of work experience in Generative AI or related fields.
Bachelor of Technology (B.E/B.Tech) degree required; M.Tech/MCA preferred.
Proficiency in Python, PyTorch, Hugging Face Transformers, and cloud platforms including Azure, AWS, or GCP.
Experience with orchestration frameworks (LangChain or similar), REST APIs (FastAPI, Flask), ML pipeline tools (MLflow, Weights & Biases), and CI/CD for ML (e.g., Azure ML, SageMaker pipelines).
Has strong hands-on experience in deploying and scaling generative AI models and frameworks within enterprise cloud environments.
Demonstrates expertise in building end-to-end ML workflows including prompt engineering, fine-tuning models, and integrating with production systems.
Operates effectively at senior associate level capable of collaborating cross-functionally with data engineers and MLOps to deliver robust AI solutions at scale.