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Tier-1 employer and Bangalore location increase competition despite senior, niche storage+ML specialization.
High because the role demands deep storage, hybrid-cloud, and production ML systems expertise specific to enterprise storage.
High due to an explicit 10+ years requirement and mandatory deep storage, ML, and architecture expertise.
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Lead architectural strategy for AI-driven analytics on telemetry data across HPE hybrid cloud storage systems impacting time-to-market and operational efficiency.
Develop and deploy advanced ML/AI models for storage optimization, predictive failure, AIOps, and generative AI workflows within global enterprise environments.
Collaborate cross-functionally to translate business challenges into analytical solutions and mentor senior technical teams to drive innovation.
Bachelor’s or Master’s in Computer Science, Data Science, Engineering, Mathematics, or related technical discipline.
10+ years of industry experience in software product development or enterprise data science with emphasis on distributed systems or cloud storage architectures.
Expertise in advanced machine learning/deep learning, programming in Python/Go, and experience with ML model deployment at scale.
Role is onsite at an HPE office as explicitly mentioned.
Technical leader with strong architectural vision in AI/ML applied to storage and hybrid cloud platforms.
Experienced in integrating generative AI (LLMs, RAG, agentic systems) for automation in enterprise storage analytics.
Proven ability to operate in complex, cross-disciplinary teams involving product, engineering, and business stakeholders.