Software Engineering Intern in San Francisco

About the Team

HP IQ's AI Machine Learning (AML) team is building the foundational platform for a new generation of agentic devices. The platform manages the full lifecycle of AI models, from creation and fine-tuning through optimized inference and intelligent orchestration. The goal is to run complex AI capabilities efficiently on-device, which reduces token costs and improves privacy.

In this internship, you will contribute to one or more core pillars of the AML platform: model inference optimization, orchestration and agent workflows, or model creation and fine-tuning. You will work closely with experienced engineers to ship features that affect HP's next-generation devices, and you will see how each part of an end-to-end AI system fits together and scales.

What You Might Do

• Work on model hosting and inference optimization, learning to profile, benchmark, and speed up model execution on resource-constrained devices. Try quantization, distillation, or other techniques to reduce latency and memory use.
• Contribute to orchestration frameworks and agent workflows, building or extending systems that coordinate multiple models and agents with tools such as LangGraph or LangChain. Build an understanding of when agentic patterns fit and how to design robust, scalable orchestrations.
• Take part in model customization and fine-tuning by adapting pre-trained language models for specific use cases. Run experiments, evaluate results, and iterate on configurations to improve performance on target tasks.
• Work with system software, design, and product teams to understand how your work fits the broader platform. Share progress, challenges, and technical decisions clearly, and seek mentorship from engineers with deep expertise in your focus area.
• Contribute to open-source projects or internal libraries related to inference, orchestration, or model training. Take ownership of end-to-end outcomes and of improving the platform's capabilities and reliability.

Preferred Skills

• Open-source contributions to inference engines (e.g., vLLM), model repositories, or orchestration libraries, with a record of contributing to a shared codebase.
• Experience with Python and ML-related 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.

Benefits

Final pay is based on factors such as job-related qualifications, education, experience, knowledge, and skills. Benefits for full-time employees include health, dental, and vision insurance, disability and life insurance, an employee assistance program, a flexible spending account, generous time off including paid parental leave, 11 paid holidays, and flexible paid vacation and sick leave.

HP, Inc. provides equal employment opportunity to all employees and applicants, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, veteran status, marital status, familial status, medical condition, pregnancy, genetic information, uniformed service status, political affiliation, or any other characteristic protected by law.