AI/ML Developer Intern

About the Role

This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

The AI/ML Developer Intern builds from the ground up to meet the needs of mission-critical applications and is always looking for innovative approaches to deliver end-to-end technical solutions to solve customer problems. Brings technical thinking to break down complex data and to engineer new ideas and methods for solving, prototyping, designing, and implementing cloud-based solutions. Collaborates with project managers and development partners to ensure effective and efficient delivery, deployment, operation, monitoring, and support of AI/ML models. The AI/ML Developer provides business value expertise to drive the development of innovative service offerings that enrich HPE's AI/ML services portfolio across multiple systems, platforms, and applications.

Key Responsibilities

• Collaborate with cross-functional teams to design, develop, and implement AI/ML 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 AI/ML 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.

Requirements & Tech Stack

• 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.
• 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.

Qualifications

• Working towards a Bachelor's and/or Master's/PhD degree with a focus in Computer Science, Data Science, Mathematics, Physics, Statistics or other related fields (Master’s degree candidates strongly preferred).
• Familiarity with and understanding of design for software systems.
• Relevant industry experience in data science and machine learning.