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# Full-Stack ML Systems Engineer

- **Company:** Success Matcher Recruitment LLC
- **Location:** Sunnyvale, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Systems Engineering, Computer Programming, Distributed Systems, Python (Programming Language), Open Source Technology, Software Engineering, Systems Integration, Tableau (Software), LangChain, Grafana, Multi-Agent Systems, Backend, Agentic-AI, CrewAI, SGLang, AutoGen, Free and Open-Source Software, Machine Learning Operations, Front End Software Development, Streamlit Framework, Semantic Kernel
- **Published:** October 26, 2026
- **Apply:** https://www.careerbuilder.com/job-details/full-stack-ml-systems-engineer-sunnyvale-ca--e0cf427c-d4de-450c-895d-37e37192b4c4

## About the Role

Systems Engineering, Startup, Systems/Internals Programming, Operating Systems, Artificial Intelligence (AI) Agents, Artificial Intelligence (AI), Software Engineering, Leadership, Research Skills, College Level Faculty, * 5+ years of production experience engineering ML systems, OR a PhD from a top-tier institution in a relevant ML Systems/Distributed Computing field., * Hands-on Agentic Frameworks: Proven experience building and deploying multi-agent applications to live production environments using frameworks like LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, ADK, or custom orchestration systems.

 * Production Scaling & Compute: Direct exposure handling scale on either the orchestration side (managing complex state, cyclical routing, and memory loops) or the infrastructure side (scaling AI compute fabrics, asynchronous jobs, queues, and container clusters).
 * Model-Serving Platforms: Practical production experience deploying and optimizing models via frameworks such as vLLM, SGLang, Ray, NVIDIA Triton, or NVIDIA Dynamo.
 * Full-Stack Implementation: Strong Python background combined with full-stack capabilities, including constructing front-end visual telemetry dashboards (using Grafana, Tableau, Streamlit, or similar).
 * Open Source Focus: Experience utilizing, developing upon, or contributing directly to open-source software repositories.

Mindset & Soft Skills

 * Enterprise Product Instincts: The ability to look at powerful backend capabilities and figure out how to make them readable, structured, and satisfying for enterprise end-users.
 * Thriving in Ambiguity: An early-stage startup mentality-comfortable shipping fast, iterative code within dynamic, shifting, and initially ill-defined parameters.
 * Clear Communication: Strong written skills to help transform complex technical primitives into clear developer documentation and clean product language.
 * A background as a Solutions Architect or Forward Deployed Engineer is a significant plus.Why You Should Join Us

## Description

* Bridge Research & Production: Work directly alongside our Chief Architect and CEO to translate cutting-edge ML systems research into an enterprise platform that product developers love to use.
 * Build the Orchestration Fabric: Design and implement full-stack ML systems for multi-agent workflow orchestration, merging deep backend systems capability with clean, satisfying developer interfaces.
 * Architect the Scaling Layer: Develop the policy-driven scaling mechanics that govern multi-agent interactions, resolving the infrastructure bottlenecks that limit agentic autonomy at scale.
 * Own the Developer Experience: Take research-grade ideas and make them legible by authoring technical documentation, code examples, sample applications, and intuitive onboarding flows.
 * Systems Integration: Collaborate across distributed systems design, networking configurations, and asynchronous event streams applied directly to runtime AI operations.