Hewlett Packard Enterprise is looking to solve customer problems by delivering end-to-end technical solutions, specifically in the area of cloud-based solutions and machine learning for wireless and wired network diagnostics, root causing, problem remediation, and optimization
Requirements
- 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
- 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
- Familiarity with design for software systems
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
Other
- 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)
- Great at communicating concepts and results; strong data visualization skills
- Relevant industry experience in data science and machine learning
- Ability to work on average 2 days per week from an HPE office
- Flexibility to manage work and personal needs
