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About HP Inc.
HP Inc. is a global technology company that develops and sells personal computers, printers, and related supplies and services. Its products include laptops, desktops, workstations, and printing solutions for consumers and businesses worldwide.
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The AI Applied Engineering Intern joins a team focused on optimizing the Agentic AI ecosystem for edge devices. In this role, you will improve the inference layer to enhance performance, efficiency, and responsiveness of models deployed on resource-constrained hardware. Your daily responsibilities include analyzing latency and memory usage, identifying bottlenecks within agentic architectures, developing software prototypes, and documenting technical designs. You will collaborate with engineering and strategy stakeholders to integrate AI models with edge hardware while utilizing development tools like Codex, Copilot, and Claude. The role requires expertise in machine learning, systems engineering, and performance optimization. By solving challenges related to deploying sophisticated AI workflows on physical devices, you will bridge the gap between software engineering and hardware integration to ensure seamless execution of agentic technologies in real-world environments.
Optimize AI inference workflows for edge-device environments to improve performance and efficiency.
Analyze latency, memory usage, and computational efficiency of AI models on resource-constrained hardware.
Identify performance bottlenecks within agentic AI architectures.
Develop and test software prototypes and optimization approaches for AI integration.
Support the integration of AI models and agents with edge hardware components.
Document technical designs, findings, and performance recommendations for stakeholders.
Utilize AI development tools like Codex, Copilot, and Claude to accelerate coding and debugging.
What we're looking for
Must be currently eligible to work in the US and not require sponsorship in the future.
Currently pursuing a bachelor's degree in Computer Science, Electrical Engineering, Mechanical Engineering, Chemical Engineering, Cybersecurity, or a related technical discipline.
Must have no more than 24 months of professional work experience related to the role (excluding internships, teaching, research, or military service).
Proficiency in artificial intelligence and machine learning.
Skills in coding, software development, and systems engineering.
Experience with AI inference, performance optimization, and edge-computing concepts.
Ability to perform technical design, prototyping, testing, debugging, and performance analysis.
Familiarity with AI development tools such as Codex, Copilot, and Claude.
Python
SQL
SQL Server
Data Pipelines
Artificial Intelligence
Machine Learning
Data Analysis
Pipeline Pilot
GitHub Copilot
software-development
Data Integration
Data Validation