Software Engineering

Who We Are

HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates.

We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless.

We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset.

By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work.

Join us as we reinvent work, so people everywhere can do their best work.

About The Role

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 LangGraph or LangChain; 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.