Software Engineering Intern, AIML Platform - HP IQ

HP • San Francisco, CA

2d

About The Position

HP IQ's AI Machine Learning (AML) team is building a foundational platform for agentic devices. The platform supports the lifecycle of AI models, including creation and fine-tuning, optimized inference, and intelligent orchestration. Its goal is to run AI capabilities efficiently on-device, enabling locally deployed agentic experiences that reduce token costs and improve privacy.

As an intern, you will contribute to one or more areas of the AML platform: model inference optimization, orchestration and agent workflows, or model creation and fine-tuning. You will work with experienced engineers on features for HP's next-generation devices and gain exposure to how components of an end-to-end AI system integrate and scale. The internship program runs from May or June through August or September 2027, with final dates based on student schedules.

Requirements

• Currently pursuing a degree in Computer Science, Engineering, or a related field, or have equivalent practical experience.
• Some coursework or project experience in machine learning, systems engineering, or software development.
• Ability to clearly articulate project goals, outcomes, challenges, and technical decisions, and explain technical concepts to peers and mentors.
• Genuine familiarity with at least one of the following: model inference and optimization, orchestration frameworks such as LangGraph or LangChain, model fine-tuning and adaptation, or similar systems-level AI work.
• Comfort working in cross-functional teams, asking for help when needed, and taking responsibility for outcomes.
• Ability to work with some ambiguity and proactively seek clarity.
• Ability to debug issues, evaluate technical tradeoffs, and make reasonable decisions among viable approaches.

Nice To Haves

• Open-source contributions to inference engines such as vLLM, model repositories, or orchestration libraries, demonstrating meaningful contributions to a shared codebase.
• Experience with Python and ML-adjacent libraries such as PyTorch, TensorFlow, Hugging Face, or FastAPI.
• Familiarity with on-device or edge AI constraints and optimization techniques.
• Experience with system-level profiling and performance optimization.
• Project experience, open-source contributions, or course projects demonstrating depth in at least one relevant area.

Responsibilities

• Work on model hosting and inference optimization, including profiling, benchmarking, and accelerating execution on resource-constrained devices.
• Experiment with quantization, distillation, and other techniques to reduce model latency and memory footprint.
• Contribute to orchestration frameworks and agent workflows, including building or extending systems that coordinate multiple models and agents using tools such as LangGraph or LangChain.
• Participate in model customization and fine-tuning by adapting pre-trained language models for specific use cases, conducting experiments, evaluating results, and iterating on configurations.
• Collaborate with system software, design, and product teams to understand how work integrates into the broader platform.
• Communicate progress, challenges, and technical decisions clearly, and seek mentorship from experienced engineers.
• Contribute to open-source projects or internal libraries related to inference, orchestration, or model training.
• Take ownership of end-to-end outcomes and help improve platform capabilities and reliability.

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• Long-term and short-term disability insurance
• Employee assistance program
• Flexible spending account
• Life insurance
• Four to twelve weeks of fully paid parental leave based on tenure
• Eleven paid holidays
• Additional flexible paid vacation and sick leave

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed