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Strong employer brand, metro location, and in-demand mid-level GenAI role drive high competition.
GenAI technical skills are transferable across industries but require ML/LLM expertise, producing medium sensitivity.
Explicit 4-7 years and many mandatory advanced ML/LLM and deployment skills make shortlisting strict.
Design, build, and deploy scalable generative AI solutions using large language models (LLMs) and transformer architectures.
Fine-tune foundation models with domain-specific datasets and optimize prompt engineering strategies to improve model responses.
Collaborate with data engineers and MLOps teams to productionize GenAI models on cloud platforms (Azure, AWS, or GCP) ensuring robustness, scalability, and compliance.
4 to 7 years of relevant work experience.
Strong expertise in Python, PyTorch, Hugging Face Transformers, and generative AI (LLMs, Transformers).
Experience deploying AI solutions on Azure, AWS, or GCP cloud platforms; familiarity with orchestration frameworks like LangChain; and ML pipeline tools such as MLflow or Weights & Biases.
Bachelor of Technology (B.E./B.Tech) degree is mandatory.
Proficient in operationalizing AI models with strong skills in ML pipeline management, CI/CD for ML, and cloud AI platforms to deliver enterprise-grade solutions.
Experienced in customizing and fine-tuning foundation models and implementing agentic AI with orchestration frameworks like LangChain or similar.
Comfortable integrating GenAI models into enterprise applications using APIs and ensuring models meet performance, scalability, and compliance standards.