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Bangalore metro and attractive ML role increase applicants, but niche LLM/finetuning skills moderate competition to medium.
Requires specialized ML, LLM, and model deployment experience, limiting transferability; high background sensitivity.
Explicit 6–9 years plus mandatory ML/LLM, deep learning, and deployment skills indicate high shortlisting strictness.
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Lead end-to-end development and operationalization of AI/ML models including supervised and unsupervised algorithms, deep learning, NLP, and LLMs.
Fine-tune Large Language Models and develop solutions using prompt engineering, RAG applications, and vector databases on cloud platforms like AWS or Azure.
Synthesize and present complex AI/ML research and technical findings to diverse business stakeholders to enable decision-making and implement AI/ML solutions.
6-9 years of relevant experience in AI/ML and software engineering roles.
Proficiency in Python and SQL programming; experience with cloud platforms such as AWS or Azure.
Hands-on experience in AI/ML model development lifecycle including data analysis, feature engineering, model building, validation, and scalability.
Experience with fine-tuning Large Language Models (LLMs), prompt engineering, Transformer architectures, and working knowledge of NLP techniques.
Experienced in deploying AI/ML solutions in production environments with emphasis on predictive modeling and operational scalability.
Capable of collaborating cross-functionally to translate business needs into AI/ML technical solutions.
Familiarity with advanced AI frameworks and orchestration tools such as PyTorch, LangChain, AutoGen, and agentic AI concepts for automation and multi-step reasoning tasks.