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Tier-1 brand, mid-level ML role, metro location, broad LLM/MLOps skillset increases applicant competition.
Core ML, LLM, and MLOps skills transfer across industries, though networking/cloud product context adds some domain specificity.
Explicit 6+ years requirement plus mandatory ML, LLM, MLOps and cloud skills tightens candidate shortlisting.
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Own the end-to-end lifecycle of AI/ML solutions for cloud applications, including design, development, deployment, and monitoring.
Build and maintain GenAI applications utilizing Large Language Models, Retrieval-Augmented Generation, and Agent workflows.
Implement and manage MLOps/LLMOps practices ensuring secure, reliable, and scalable AI deployments in collaboration with cross-functional teams.
Bachelor's degree in computer science, engineering, information systems, or closely related quantitative discipline; Master's degree desirable.
Minimum 6 years of professional experience with hands-on expertise in AI/ML technologies specified.
Proficiency in Python, SQL, ML/DL frameworks (Scikit-learn, PyTorch/TensorFlow), cloud platforms (AWS, Azure, or GCP), containerization (Docker, Kubernetes) and MLOps tools.
Hybrid work mode with required onsite presence approximately 2 days per week at HPE office.
Experienced in architecting and delivering complex AI/ML and GenAI cloud-native solutions with a focus on operational excellence and security.
Comfortable leading technical decisions and mentoring others in a cross-functional environment involving both business and engineering stakeholders.
Strong background in modern AI evaluation, monitoring tools, and deployment of scalable AI services using best DevOps/MLOps practices.