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Mid-level ML manager role in Bengaluru with broad LLM/MLOps requirements and common Data Scientist title.
Specialized LLM, graph, and production ML skills transferable, but BU-specific agentic AI context adds sensitivity.
Explicit 5+ years overall, 3+ years ML requirement plus LLM/graph/cloud tech needs raises strictness.
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Own domain-specific model evaluation, fine-tuning, and operationalization for agentic AI workflows and LLM solutions.
Design and implement evaluation frameworks, taxonomies, and metrics for model benchmarking and anomaly detection.
Build and deploy scalable AI solutions including knowledge graphs, embeddings, and inference engines in production environments.
Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
5+ years overall IT experience with 3+ years applied machine learning or NLP experience in production environments.
Strong technical skills in LLMs, fine-tuning, evaluation, Python, ML libraries (PyTorch, TensorFlow, Scikit-learn), and graph databases (e.g., Neo4j, DGL).
Experience with cloud AI/ML platforms (AWS, Azure, or GCP) and MLOps practices.
Experienced in leading AI/ML initiatives focused on agentic AI platforms and domain-specific LLM solutions.
Proficient in designing evaluation frameworks and operationalizing advanced models including generative AI and knowledge graph integrations.
Capable of collaborating across engineering, product, and business teams to deploy robust production-scale AI solutions.