ML Infrastructure Engineer

Graphon AI is building a pre-model intelligence layer and context engine for next-generation AI systems. The ML Infrastructure Engineer will build and scale production machine learning infrastructure, including training pipelines, inference and serving systems, data pipelines, and model deployment, while working with modern ML stacks and distributed systems.

Responsibilities:

• Strong software engineering fundamentals with experience building production systems (Python required; experience with C++/Go a plus)
• Experience working with machine learning infrastructure, such as training pipelines, inference/serving systems, data pipelines, or model deployment
• Familiarity with modern ML stacks (e.g., PyTorch/JAX, GPUs, distributed training or inference)
• Solid understanding of core systems concepts (version control, Linux, basic networking, CI/CD)
• High agency and ownership mindset—you identify problems, propose solutions, and drive execution
• Pragmatic, “right tool for the job” thinker who enjoys collaborating and iterating quickly
• Experience scaling ML systems in production environments
• Experience with distributed systems, large-scale data processing, or GPU optimization
• Exposure to multimodal ML, retrieval systems, or graph-based representations
• Prior startup experience or comfort operating in ambiguous, fast-moving environments