Software Engineering Intern — LLM Systems
7 days ago
Software Engineering Intern — LLM Systems & Applied AI Engineering
Supervisory Org:
Security GenAI
About the Job
We're looking for a Software Engineering Intern passionate about building systems that make Large Language Models (LLMs) work in the real world. You'll help design and implement backend components, APIs, and pipelines that connect models to applications, enabling fine-tuning, inference, evaluation, and monitoring at scale.
You'll join a fast-moving team working at the intersection of software engineering and AI, where every service you build helps make intelligent systems faster, safer, and more reliable. Our environment blends Go, Python, and C++ (bonus) for high-performance backend development, paired with tools and frameworks for LLM inference and experimentation.
This is a 12-week full-time internship where you'll work on high-impact projects that directly contribute to our mission. We're seeking motivated students who want to apply their technical and research skills to shape the future of responsible AI. Please note this is an on-site internship based in our San Jose, California office.
Your Key Responsibilities:
- Design and implement backend components to support LLM inference and evaluation.
- Integrate model endpoints into APIs and services powering real-world applications.
- Contribute to tooling for fine-tuning, model orchestration, and inference performance optimization.
- Build monitoring and analytics layers to track model responses, latency, and reliability.
- Collaborate with ML engineers on serving pipelines, prompt evaluation, and guardrail logic.
- Prototype and ship features that connect models to production-grade systems.
To qualify, You Must:
- Be actively enrolled in a university program pursuing a Bachelor's, Master's, or PhD degree in Computer Engineering, or a related discipline in United States for the entire duration of the internship.
- Be graduating between December June 2027.
- Be available from May August 2026 OR June September 2026.
Preferred Qualifications
- Proficiency in Go and/or Python.
- Solid understanding of software engineering fundamentals and API design.
- Exposure to LLM frameworks such as Hugging Face, vLLM, OpenAI API.
- Interest in model fine-tuning, evaluation pipelines, and prompt optimization.
- Familiarity with inference performance concepts (token throughput, latency, caching).
- Curiosity about how backend systems bring AI models to life — from request to response.
- Self-driven mindset and eagerness to learn across AI and systems boundaries.
What You'll Gain:
- Hands-on experience with LLM model integration, fine-tuning, and inference systems.
- Deep understanding of how AI models are deployed, scaled, and evaluated in production.
- Mentorship from engineers building real-world AI infrastructure and safety systems.
- A collaborative, fast-paced environment where you can experiment, learn, and grow quickly.
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