Machine Learning Systems Engineer

Senior Full-Stack ML Systems Engineer (Founding Team, Employee #4) Location: Sunnyvale, CA (Onsite with some flexibility) Compensation: $150,000 – $230,000 + up to 1% equity The Opportunity I am partnering with an early-stage, deeply technical AI infrastructure startup building the technology to solve one of the hardest unsolved problems in AI: closing the gap between building agentic applications and actually scaling them efficiently. Their platform automates the entire workflow intelligence layer, providing policy-driven scaling for multi-agentic systems. This is not another thin LLM wrapper. The core technology is backed by deep systems research involving distributed systems, software-defined networking concepts, and OS-level primitives applied to AI workflow orchestration. As Employee #4, the successful candidate will work directly alongside a world-class founding team—including a 3x founder (PhD, ex-Bell Labs, ex-Qualcomm) and a world-renowned ML systems researcher and university chair professor. The Role Working closely with the CEO and Chief Architect, this engineer will turn complex ML systems research into a highly polished product that developers and enterprises enjoy using. This requires a rare blend of deep backend systems engineering, multi-agent orchestration, and strong full-stack visualization capabilities. Core Responsibilities Translate research-grade backend capabilities into legible, useful, and satisfying product features for developers. Architect and scale multi-agentic systems and model-serving platforms. Assist with the development of documentation, onboarding flows, and product language to simplify complex technical concepts. Qualifications 5+ years of professional software engineering experience. Hands-on experience developing multi-agentic systems using frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, or custom-built agent systems. Experience utilizing model-serving platforms like vLLM, SGLang, Ray, or NVIDIA Triton/Dynamo. Strong full-stack development skills, with a specific emphasis on frontend visualization using tools like Grafana or Tableau. Strong background with APIs, distributed systems, async jobs, queues, containers, and cloud infrastructure. Self-driven mindset with the ability to thrive in an ambiguous, early-stage startup environment. Preferred Pluses Experience deploying multi-agentic systems into a live production environment. Active contributions to open-source software. Prior experience working as a Solutions Architect or Forward Deployment Engineer. Technical Stack Python, LangGraph, LangChain, AutoGen, CrewAI, vLLM, SGLang, Ray, NVIDIA Triton/Dynamo, Distributed Systems, Software Defined Networking, Docker, Kubernetes, Cloud Infrastructure, Tableau, Grafana, MCP. Show more Show less