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Tier-1 brand plus Bangalore metro increase competition, offset by seniority and niche storage-ML specialization.
Deep storage, distributed systems, and ML specialization reduce cross-industry transferability.
Explicit 10+ years requirement and specialized storage plus ML expertise make hiring filters highly selective.
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Lead architectural strategy for data science and analytics within HPE's hybrid cloud and storage systems, focusing on telemetry data pipelines from enterprise storage.
Develop and deploy advanced AI/ML models (including generative AI) for predictive infrastructure management, storage optimization, and automated troubleshooting.
Collaborate cross-functionally to translate business challenges into production analytics solutions and mentor senior engineers and data scientists across teams.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.
10+ years of industry experience in software product development or enterprise data science with emphasis on distributed systems, storage, or cloud infrastructure.
Expertise in machine learning algorithms, deep learning frameworks, and programming in Python and Go-lang; experience with C/C++ is a strong plus.
Role is onsite primarily in an HPE office.
Experienced technical leader skilled at bridging advanced AI/ML techniques with large-scale hybrid cloud and storage platforms.
Demonstrated ability to architect and deploy scalable machine learning pipelines and generative AI workflows integrated with enterprise-grade telemetry data.
Proven track record in cross-functional collaboration and mentoring within complex, distributed engineering environments spanning hardware and software domains.