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Tier-1 brand, Bangalore location, mid-level (4–7 yrs), popular GenAI role with broad toolset.
Core GenAI and LLM engineering skills are transferable across industries but require specialized model and cloud experience.
Explicit 4–7 year requirement plus mandatory PyTorch, Hugging Face, cloud, LangChain and ML pipeline skills.
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Design, build, and deploy scalable Generative AI solutions using large language models (LLMs) and transformer architectures.
Customize and fine-tune foundation models with domain-specific data and implement prompt engineering strategies to optimize responses.
Collaborate with cross-functional teams to productionize GenAI models on cloud platforms (Azure/AWS/GCP) and integrate AI capabilities into enterprise applications via APIs.
4 to 7 years of relevant work experience in Generative AI or related fields.
Proficient in Python, PyTorch, Hugging Face Transformers, and orchestration frameworks like LangChain.
Experience deploying ML solutions on cloud platforms such as Azure, AWS, or GCP, with knowledge of CI/CD practices for ML pipelines (e.g., Azure ML, SageMaker).
Bachelor’s degree in Technology (B.E/B.Tech) or equivalent (M.Tech/MCA also acceptable).
Experienced in end-to-end development and deployment of LLM-based GenAI solutions with practical knowledge of fine-tuning and prompt engineering.
Comfortable working in cloud environments and familiar with ML pipeline and orchestration tools, enabling seamless productionization and scaling.
Skilled in API development and integration to embed Generative AI capabilities into enterprise settings, demonstrating operational ownership of AI product features.