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Software Engineering Intern, AIML Platform - HP IQ

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Hewlett Packard Co.
Full Time, Apprenticeship/Internship position
Listed on 2026-11-05
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Software Engineer
Salary/Wage Range or Industry Benchmark: 40 - 50 USD Hourly USD 40.00 50.00 HOUR
Job Description & How to Apply Below
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Software Engineering Intern, AIML Platform - HP IQApply:
San Francisco, California, United States of America:
Full time:
Posted Today:
End Date:
December 31, 2026 (30+ days left to apply):
UNI
4800

Software Engineering Intern, AIML Platform - HP IQ
** Description
- ** HP IQ's AI Machine Learning (AML) team is building the foundational platform powering a new generation of agentic devices. This platform orchestrates the complete lifecycle of AI models: from creation and fine-tuning through optimized inference and intelligent orchestration. The team works to make complex AI capabilities run efficiently on-device, enabling locally-deployed agentic experiences that reduce token costs and improve privacy.

In this internship role, 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 partner closely with experienced engineers to ship features that directly impact HP's next-generation devices and gain visibility into how each component of an end-to-end AI system integrates and scales.
** What You Might Do
*** Work on model hosting and inference optimization, learning how to profile, benchmark, and accelerate model execution on resource-constrained devices; experiment with quantization, distillation, or other optimization techniques to reduce latency and memory footprint.
* Contribute to orchestration frameworks and agent workflows, building or extending systems that coordinate multiple models and agents using tools like Lang Graph or Lang Chain; develop an understanding of when agentic patterns are appropriate and how to design robust, scalable orchestrations.
* Participate in model customization and fine-tuning, taking pre-trained language models and adapting them for specific use cases; conduct experiments, evaluate results, and iterate on model configurations to improve performance for target tasks.
* Collaborate cross-functionally with system software, design, and product teams to understand how your work integrates into the broader platform; communicate 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 relevant to inference, orchestration, or model training; demonstrate ownership of end-to-end outcomes and ownership of improving the platform's capabilities and reliability.
** Essential Qualifications
*** Currently pursuing a degree in Computer Science, Engineering, or related field, or equivalent practical experience. Some coursework or project experience in machine learning, systems engineering, or software development is expected.
* Demonstrated technical communication skills: ability to articulate project goals, outcomes, challenges, and technical decisions clearly; comfort explaining technical concepts to peers and mentors.
* Genuine familiarity with one or more of the following: model inference and optimization, orchestration frameworks (Lang Graph, Lang Chain), model fine-tuning and adaptation, or similar systems-level AI work. Project experience, open-source contributions, or course projects demonstrating depth in at least one area are highly valued.
* Collaboration and ownership mindset: comfort working in cross-functional teams, asking for help when needed, and taking responsibility for outcomes; ability to operate with some ambiguity and seek clarity proactively.
* Problems-solving orientation: ability to debug issues, evaluate technical tradeoffs, and make reasonable decisions when multiple approaches are viable.
** Preferred Skills
*** Open-source contributions to inference engines (e.g., vLLM), model repositories, or orchestration libraries; demonstrated ability to contribute meaningfully to a shared codebase.
* Experience with Python and ML-adjacent libraries (PyTorch, Tensor Flow, Hugging Face, FastAPI, or similar).
* Familiarity with on-device or edge AI constraints and optimization techniques.
* Experience with system-level profiling and performance optimization.
*** Hourly Pay Range:**…
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