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Strong employer brand, metro Bangalore, and mid-senior ML role with niche LLM requirements drive moderate competition.
Requires specialized LLM, NLP, graph, and production ML expertise, reducing cross-industry transferability.
Explicit years plus mandatory LLM, graph DB, and production MLOps skills create strict shortlisting.
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Drive applied research and product-oriented data science for Agentic AI platform initiatives, focusing on domain-specific model evaluation, fine-tuning, and operationalization.
Lead design and implementation of evaluation frameworks, model benchmarking, anomaly detection, and development of knowledge graphs and inference engines.
Collaborate with engineering and product teams to deploy scalable AI/ML solutions in production and communicate findings across teams.
Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
5+ years overall IT experience, with 3+ years in applied machine learning or NLP in production environments.
Strong experience with LLMs, generative AI, NLP including fine-tuning and evaluation.
Proficiency in Python and ML libraries (PyTorch, TensorFlow, Scikit-learn); experience with graph databases and cloud AI/ML services (AWS, Azure, or GCP).
Experienced in working independently on domain-specific AI/ML problem statements and managing end-to-end model lifecycle in production-scale environments.
Deep expertise in LLMs, graph-based reasoning, and agentic AI systems aligned with platform engineering and business needs.
Proven ability to collaborate cross-functionally with engineering, product, and business teams to deliver operational AI solutions.