AI Engineer

Employment Type: Full-time Location Type: Onsite

Who We Are:

Hewlett Packard Enterprise (HPE) is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world.

Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career, our culture will embrace you. Open up opportunities with HPE.

Job Description:

HPE Operations is our innovative IT services organization. It provides the expertise to advise, integrate, and accelerate our customers’ outcomes from their digital transformation. Our teams collaborate to transform insight into innovation. In today’s fast-paced, hybrid IT world, being at business speed means overcoming IT complexity to match the speed of actions to the speed of opportunities. Deploy the right technology to respond quickly to market possibilities. Join us and redefine what’s next for you.

This role has been designed as "Onsite" with an expectation that you will primarily work from an HPE office.

Key Responsibilities:

• Develops and programs integrated software algorithms to structure, analyze, and leverage structured and unstructured data in product and systems applications.
• Works with large-scale computing frameworks, data analysis systems, and modeling environments.
• Uses machine learning and statistical modeling techniques to improve product/system performance, data management, quality, and accuracy.
• Formulates descriptive, diagnostic, predictive, and prescriptive insights/algorithms and translates technical specifications into code.
• Applies, optimizes, and scales deep learning technologies and algorithms to give computers the capability to visualize, learn, and respond to complex situations.
• Documents procedures for installation and maintenance, completes programming, performs testing and debugging, defines and monitors performance metrics.
• Contributes to the success of HPE by translating customer requirements and industry trends into AI/ML products, solutions, and systems improvement projects.

Management Level Definition:

Contributions include applying intermediate-level subject matter expertise to solve common technical problems. Acts as an informed team member providing analysis of information and recommendations for appropriate action. Works independently within an established framework and with moderate supervision.

What You Will Do:

• Model Development: Primary responsibility will be to design, develop, and implement machine learning models and algorithms. This involves researching, experimenting, and selecting appropriate models and techniques to solve specific business problems.
• Data Preparation: Responsible for preparing and pre-processing large datasets for machine learning tasks. This includes data cleaning, normalization, feature extraction, and transformation to ensure the data is suitable for training and testing machine learning models.
• Model Training & Evaluation: Will train machine learning models using appropriate algorithms and frameworks. This involves selecting and optimizing hyperparameters, cross-validating the models, and evaluating their performance using various metrics such as accuracy, precision, recall, and F1-score.
• Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, and stakeholders, to understand business requirements, gather feedback, and iterate on models and solutions. Effective communication and the ability to explain complex concepts to non-technical stakeholders are crucial in this role.
• Design Review: Contribute to small sections of design review sessions, presenting your work and gathering feedback from the engineering manager or team leader.