ML Systems Intern at Canyon Code in Sunnyvale, CA

Summary: Canyon Code is an AI infrastructure company focused on frontier artificial intelligence software. The ML Systems Intern will work with the Chief Architect and CEO to turn machine learning systems research into a developer- and enterprise-ready product, contributing across multi-agent systems, model serving, full-stack development, and cloud infrastructure.

Responsibilities:
- Developed multi-agentic systems using LangGraph, AutoGen, CrewAI, Semantic Kernel, or custom agent systems
- Deployed multi-agentic systems into live production. Plus
- Used model-serving platforms such as vLLM, SGLang, Ray, or NVIDIA Dynamo
- Strong full-stack development skills, especially front-end and data visualization (Tableau, Grafana, etc.)
- Used and built upon open-source software
- Contributed to open-source projects. Plus
- Good product instincts: can take a powerful backend capability and make it legible, useful, and satisfying for developers
- Experience as a Solutions Architect or Forward Deployment Engineer. Plus
- Familiar with APIs, distributed systems, async jobs, queues, containers, and cloud infrastructure
- Self-driven; thrives in early-stage, ambiguous, fast-moving environments
- Clear written communication: can turn research-grade ideas into docs, examples, onboarding flows, and product language
- Work on Frontier AI
- Shape software that will redefine what's possible for AI infrastructure
- Collaborate directly with the founding team and get a hand in shaping the vision of the company
- Collaborate with industry leaders at the forefront of AI infrastructure software

Required Qualifications:
- Developed multi-agentic systems using LangGraph, AutoGen, CrewAI, Semantic Kernel, or custom agent systems
- Used model-serving platforms such as vLLM, SGLang, Ray, or NVIDIA Dynamo
- Strong full-stack development skills, especially front-end and data visualization (Tableau, Grafana, etc.)
- Used and built upon open-source software
- Good product instincts: can take a powerful backend capability and make it legible, useful, and satisfying for developers
- Familiar with APIs, distributed systems, async jobs, queues, containers, and cloud infrastructure
- Self-driven; thrives in early-stage, ambiguous, fast-moving environments
- Clear written communication: can turn research-grade ideas into docs, examples, onboarding flows, and product language

Preferred Qualifications:
- Deployed multi-agentic systems into live production. Plus
- Contributed to open-source projects. Plus
- Experience as a Solutions Architect or Forward Deployment Engineer. Plus

Required Skills: Multi-Agent Systems, LangGraph, AutoGen, CrewAI, Semantic Kernel, vLLM, SGLang, Ray, NVIDIA Dynamo, Full-Stack Development, Distributed Systems, Cloud Infrastructure

Benefits: Work on Frontier AI, Collaborate directly with the founding team and get a hand in shaping the vision of the company., Collaborate with industry leaders at the forefront of AI infrastructure software.