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Popular mid-senior ML role in Bangalore with broad, non-niche requirements increases candidate competition.
ML/AI skills are transferable but LLM/agent production experience raises domain specificity.
Explicit 6–10 years plus mandatory LLM, RAG, AWS, and productionization skills make filters strict.
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Design and develop advanced ML models and end-to-end pipelines utilizing structured and unstructured data.
Lead AI solutions development involving Large Language Models, Retrieval-Augmented Generation, and agentic AI platforms.
Collaborate to deploy, monitor, and optimize ML and AI systems impacting product strategy, adoption, and revenue growth.
6 to 10 years of experience in Data Science, Machine Learning, or related roles.
Strong proficiency in Python and SQL; experience with ML frameworks such as Scikit-learn, Pandas, NumPy, SciPy, Hugging Face.
Hands-on experience deploying and monitoring ML models and AI systems on AWS; familiarity with Azure or GCP is a plus.
Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
Proven ability to operationalize AI/ML models including GenAI applications with LLMs and vector databases for production environments.
Experience working cross-functionally to translate complex business problems into scalable AI/ML solutions that drive product engagement and revenue.
Background in SaaS metrics and implementing analytics for product usage, adoption, and monetization strategies in Agile settings.