About the Company

Hewlett Packard Enterprise (HPE) is a global edge-to-cloud technology company that helps organizations connect, protect, analyze, and manage their data and applications. HPE develops technology solutions that help businesses turn data into actionable insights and improve how they operate. The company values innovation, collaboration, professional development, and an inclusive workplace where employees can grow and contribute to meaningful technology advancements.

About the Role

HPE is seeking a Principal AI Engineer to lead the development and deployment of advanced artificial intelligence and machine learning solutions. This senior-level role focuses on building scalable AI systems, developing sophisticated algorithms, and applying statistical modeling and deep learning to improve product performance, data quality, and system capabilities. You will work closely with data scientists, software engineers, product managers, and engineering leaders to translate customer needs and industry developments into practical AI solutions. The role also includes technical leadership, research, design reviews, mentoring, and collaboration on long-term engineering strategies. The ideal candidate brings extensive AI and machine learning experience, strong programming and mathematical skills, and the ability to solve complex technical problems while guiding other engineers.

Key Responsibilities

Design, develop, train, evaluate, and deploy advanced machine learning models and algorithms. Select appropriate modeling techniques, prepare and preprocess data, perform feature engineering, and evaluate model performance. Lead research initiatives to explore emerging AI technologies, test new algorithms, and identify opportunities for innovation. Design scalable AI system architectures that support performance, reliability, and efficient deployment. Optimize algorithms and use distributed computing frameworks and cloud services to build effective AI solutions. Collaborate with data scientists, software engineers, product managers, and other teams to identify opportunities for AI integration and provide technical guidance. Apply data mining, data modeling, natural language processing, and machine learning techniques to extract insights from structured and unstructured datasets. Provide technical leadership and mentorship to junior engineers, review their work, and promote engineering best practices. Lead design reviews across projects to ensure consistency, technical quality, and alignment with established standards. Partner with engineering managers and team leads to establish long-term design and implementation strategies. Develop feedback loops and continuous improvement processes to strengthen AI systems and engineering practices. Lead technical meetings, track progress, coordinate teams, and help resolve project issues. Prepare and deliver technical presentations and reports to executive stakeholders, explaining complex AI strategies and their business impact. Document installation and maintenance procedures, write and test code, debug software, and define and monitor performance metrics. Contribute to solutions for complex application, system administration, or network-related problems when relevant to the role.

Required Qualifications

Bachelor's or master's degree in Computer Science, Engineering, Data Science, Machine Learning, Artificial Intelligence, or a closely related quantitative discipline. At least eight years of experience in artificial intelligence and machine learning. Strong understanding of supervised and unsupervised learning, deep learning, reinforcement learning, natural language processing, computer vision, and statistical modeling. Experience implementing and deploying machine learning algorithms, including decision trees, random forests, support vector machines, and neural networks. Proficiency with Python, Java, or C++ and the ability to write clean, efficient, and maintainable code. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. Strong knowledge of data preparation, data cleaning, feature extraction, dimensionality reduction, missing-value handling, and data quality management. Solid mathematical foundations in linear algebra, calculus, probability, and statistics. Strong communication skills and the ability to explain complex technical concepts to technical and non-technical audiences. Experience guiding and mentoring engineers and providing technical direction to cross-functional teams. Preferred Qualifications / Requirements Expertise in deep learning architectures and techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). Experience with data visualization tools and communicating model insights effectively. Familiarity with Git, software testing methodologies, software engineering principles, and Agile development practices. Experience leading AI research initiatives, publishing research papers, or contributing to open-source AI projects. A commitment to continuous learning and staying current with advances in AI and machine learning. Salary & Benefits The expected base salary range is $157,000–$361,000 per year for eligible locations in Georgia, Illinois, North Carolina, and Wisconsin, as well as Texas. Actual compensation may vary based on geographic location, experience, education, training, and skill level. Variable incentives may also be offered. HPE provides a comprehensive benefits package designed to support employees' physical, financial, and emotional well-being. The company also offers professional development programs and opportunities for career growth. The position is designated as remote/teleworker, with the employee primarily working from home. Equal Employment Opportunity Hewlett Packard Enterprise is an equal opportunity employer and does not discriminate based on protected characteristics. The company is committed to an inclusive workplace and considers employment decisions based on qualifications, merit, and business needs. HPE also provides reasonable accommodations for qualified applicants with disabilities during the application and interview process.