Join Canyon Code as a Full-Stack ML Systems Engineer to work on AI Infrastructure software, developing multi-agentic systems and deploying them into live production. You will work directly with the Chief Architect and CEO to turn ML systems research into a product. Key requirements include 4+ years of professional software engineering experience, strong full-stack development skills, and experience with model-serving platforms.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
About Canyon Code
Canyon Code is a Silicon Valley start-up that is tackling some of the stickiest problems in the AI Infrastructure software space. The company’s workflow intelligence layer is a breakthrough technology that gives enterprises the controls to optimize and manage each AI workflow at scale.
About The Role
We are looking for a full-stack ML systems engineer to work directly with Canyon Code's Chief Architect and the CEO to turn ML systems research into a product that developers and enterprises enjoy using.
You are a good fit if:
- You have 4+ years of professional software engineering experience.
- You have developed multi-agentic systems using multiple tool stacks e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel, or custom agent systems.
- PLUS: You have deployed multi-agentic systems into live production
- You have used model-serving platforms e.g., vLLM, SGLang, Ray, NVIDIA Dynamo
- You have strong full-stack development skills. Especially front-end, including visualization via Tableau, Grafana etc.
- You have used and developed-upon open source software
- PLUS:You have contributed to open-source software
- You have good product instincts: you can take a powerful backend capability and make it legible, useful, and satisfying for developers.
- PLUS: You have worked as Solutions Architect or a Forward Deployment Engineer
- You have experience with APIs, distributed systems, async jobs, queues, containers, deployment systems, or cloud infrastructure.
- You are self-driven and can thrive in ill-defined, ambiguous, dynamic, early-stage work.
- You possess clear written communication. You will help turn research-grade ideas into docs, examples, onboarding flows, and product language.
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Why Join
You will gain working experience in tackling one of the most topical problems in the intersection of AI Infrastructure software, Enterprise multi-agentic scaling and MLOps-aware developer tool development.
- Dual Consideration → We will consider candidates both for intern as well as full-time roles depending on fit.
- Path to Sponsorship → High-performing interns have the opportunity to convert into full-time roles with H1-B sponsorship (if needed)
- Work on Frontier AI → Shape software that will redefine what’s possible for AI Infra.
- Mentorship → Direct guidance from a founding team with deep experience in ML Systems research and AI Infra. platforms platforms.
- Visibility & Networking → Collaborate with industry leaders at the forefront of AI Infra. software.
Contact: info@canyoncode.ai
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