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Tier-1 brand, Bangalore metro, mid-level role, but specialized GenAI skills moderate applicant competition.
GenAI technical skills are transferable across industries but require ML-specific expertise, so sensitivity is medium.
Explicit 4–7 years plus mandatory LLM, PyTorch, cloud and MLOps skills create high shortlisting strictness.
Design, develop, fine-tune, and deploy scalable Generative AI solutions using large language models (LLMs) and transformer architectures.
Build intelligent applications with GenAI integration into enterprise systems, collaborating with data engineers and MLOps teams for production deployment on Azure, AWS, or GCP.
Implement and optimize AI model workflows using orchestration frameworks like LangChain, develop APIs with FastAPI or Flask, and manage ML pipelines with MLflow or Weights & Biases ensuring robustness and compliance.
4 to 7 years of relevant work experience in Generative AI development.
Mandatory expertise in Python, PyTorch, Hugging Face Transformers, and GenAI (LLMs, Transformers).
Experience deploying GenAI solutions on cloud platforms such as Azure, AWS, or GCP with knowledge of CI/CD tools like Azure ML or SageMaker pipelines.
Bachelor's degree in Technology (B.E/B.Tech) or related field (M.Tech/MCA also acceptable).
Experienced in productionizing GenAI models with strong skills in orchestration frameworks (e.g., LangChain) and API development.
Able to work effectively in cross-functional teams including data engineers and MLOps specialists in cloud environments.
Up-to-date with the latest GenAI research and comfortable with iterative model performance evaluation and improvement.