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San Jose, California, United States of America

Internship

Hybrid

$35/hr - $46/hr

Intern

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. The AI/ML Intern role involves collaborating with cross-functional teams to design and implement cloud solutions while applying machine learning techniques to solve complex problems in network diagnostics and optimization.

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Responsibilities

Collaborate with cross-functional teams to design, develop, and implement cloud solutions tailored to meet business needs.
Works with domain experts to identify and formalize machine learning problems for wireless and wired network diagnostics, root causing, problem remediation, and optimization
Design, implement, and validate machine learning algorithms on big data
Guide and oversee deployment of implemented machine learning solutions and monitor their operation
Use Agentic AI to solve networking problems
Identifies, debugs and creates solutions for issues with code and integration into application architecture
Develops and executes comprehensive test plans for features adhering to performance, scale, usability, and security requirements.
Deploy cloud-based systems and applications code using continuous integration/deployment pipelines
Contributes towards innovation and integration of new technologies into projects
Analyzes science, engineering, business, and other data processing problems to develop and implement solutions to complex application problems, system administration issues, or networking

Qualification

Required

Working towards a Bachelor's and/or Master's degree with a focus in Computer science, Data Science, or other related fields (Master’s degree candidates strongly preferred)
Familiarity with and understanding of design for software systems
Proficient Python coder (PySpark, Scikit-learn), experience with software engineering best practices
A basic understanding of Object-Oriented Programming (OOP)
Strong background in statistical and machine learning techniques such as anomaly detection, clustering and ranking of events, time series analysis, event stream mining, hypothesis testing, causal inference, and deep learning
Great at communicating concepts and results; strong data visualization skills
Relevant industry experience in data science and machine learning
Experience with online learning algorithms, reinforcement learning, semi-supervised learning, or mixed time-series/event streams
Familiarity with GenAI and large language models (LLMs). Agentic AI is a plus