HP
AI Applied Engineering Intern
Vancouver, Washington, United States of America · Internship · Posted Oct 2, 2026
- Experience
- No more than 24 months of professionally related prior work experience; internships, teaching assistance, research work, and military experience are excluded.
- Education
- Currently pursuing a bachelor’s degree in Computer Science, Electrical Engineering, Mechanical Engineering, Chemical Engineering, Cybersecurity, or a related technical discipline.
- Visa sponsorship
- Candidates must be currently eligible to work in the US and must not require future work authorization sponsorship. HP will not assist with or sign documentation for immigration sponsorship, including CPT or OPT.
About the job
Optimizes HP’s agentic AI inference workflows for edge devices, improving model performance and deployment on resource-constrained hardware.
What you'll do
- Analyze inference latency, memory use, computational efficiency, and model performance; identify bottlenecks.
- Develop and test software prototypes and optimization approaches, and support AI model and agent integration with edge hardware.
- Document technical findings and recommendations, and collaborate with engineering and strategy teams.
What they ask for
- Currently pursuing a bachelor’s degree in Computer Science, Electrical Engineering, Mechanical Engineering, Chemical Engineering, Cybersecurity, or a related technical discipline.
- No more than 24 months of professionally related prior work experience, excluding internships, teaching assistance, research work, and military experience.
- Able to obtain US work authorization in 2027 and not require sponsorship in the future.
- Skills in AI and machine learning, coding and software development, inference optimization, systems engineering, prototyping, testing, debugging, and performance analysis.
Pay
USD $29 to $35 per hour (hourly pay)
Tools
Codex, Copilot, Claude
AI focus
Applies and optimizes agentic AI inference for edge devices, including performance analysis, bottleneck identification, and integration with edge hardware.
Model-written summary · the original posting is authoritative