Principal AI Engineer

🕒 October 20

🌽 Illinois, North Carolina, +2 more states – Remote

🌽 Illinois – Remote 🌲 North Carolina – Remote 🤠 Texas – Remote 🧀 Wisconsin – Remote

💵 $157k - $361k / year

⏰ Full Time

🔴 Lead

🤖 AI Engineer

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Hewlett Packard Enterprise

WebsiteLinkedInAll Job Openings

10,000+ employees

🏢 Enterprise

🔧 Hardware

🤖 Artificial Intelligence

💰 $1.5G Post-IPO Equity - Hewlett Packard Enterprise on 2025-04

Enterprise • Hardware • Artificial Intelligence

Hewlett Packard Enterprise is an enterprise-focused technology company that delivers infrastructure, software, and services to help organizations build, manage, and secure hybrid cloud and AI-enabled environments. The company’s offerings — reflected in the provided text — include servers and high-performance computing (HPE ProLiant, HPE Cray), enterprise storage (HPE Alletra), networking products and services (HPE Aruba, Juniper partnership), AI platforms and turnkey AI factories, hybrid cloud and as-a-service offerings (GreenLake), security and networking (Zero Trust, SASE), and a broad portfolio of professional, advisory, and support services. HPE positions itself as a partner for large organizations modernizing data centers, deploying AI at scale, and adopting hybrid cloud operations.

📋 Description

• Design, develop, and deploy advanced machine learning models and algorithms • Select techniques, preprocess data, engineer features, train models, and evaluate performance • Lead research initiatives, conduct experiments, evaluate algorithms, and identify innovation opportunities • Design AI system architecture for scalability, performance, and reliability • Optimize algorithms and leverage distributed computing frameworks and cloud services • Collaborate with data scientists, software engineers, and product managers to identify AI integration opportunities • Provide technical guidance, leadership, and mentorship to junior engineers • Oversee design review sessions across projects and ensure adherence to best practices • Establish long-term design and implementation strategies with the engineering manager and team lead • Lead feedback loops and continuous improvement processes • Lead meetings, track progress, resolve issues, and coordinate teams • Present technical strategies and business impact to executive stakeholders • Apply data mining, data modeling, natural language processing, and machine learning to analyze datasets • Contribute to complex application, system administration, or network solutions where applicable

🎯 Requirements

• Bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline • 8+ years of experience in AI and Machine Learning • Solid 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 • Knowledge of TensorFlow, PyTorch, or scikit-learn • Expertise in deep learning techniques, architectures, and frameworks, including CNNs, RNNs, and GANs • Proficiency in Python, Java, or C++ • Experience with data wrangling, feature extraction, dimensionality reduction, missing-value handling, and data quality • Understanding of linear algebra, calculus, probability theory, and statistics • Proficiency in data visualization tools and techniques • Familiarity with software engineering principles, Git, testing methodologies, and agile development practices • Experience leading research initiatives, publishing research papers, or contributing to open-source AI projects • Experience guiding and mentoring other engineers • Strong communication skills for cross-functional collaboration, technical leadership, and mentorship

🏖️ Benefits

• Comprehensive health and wellbeing benefits supporting physical, financial, and emotional wellbeing • Personal and professional development programs • Flexible work arrangements to manage work and personal needs • Remote/teleworker work arrangement • Variable incentives may also be offered

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