{"schemaVersion":"jobsearcher.job.v1","id":"8bbc6a2c52ecb98a103faced","url":"https://jobsearcher.com/jobs/8bbc6a2c52ecb98a103faced","canonicalUrl":"https://jobsearcher.com/jobs/8bbc6a2c52ecb98a103faced","title":"Machine Learning Engineer (Systems)","description":"Salary: $150k to $250k\n\nEquity: Up to 1% equity\n\nOn-site work policy\n\nSunnyvale, CA onsite with some flexibility on a case-by-case basis.\n\nFull-time position\n\nLocation\n\nSaratoga, California, San Francisco Bay Area, California\n\nVisa sponsorship details\n\nOpen to visa transfers (e.g. OPT, H1B transfers)\n\nAdditional visa sponsorship details\n\nH1B transfers, new H1B applications, TN visas\n\nUs citizen and permanent residents\n\n5+ years of experience\n\n5+ years in ML systems engineering in production (academic years can substitute if PhD from top institution in relevant ML systems field)\n\nTech stack\n\nLangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, Google ADK, vLLM, SGLang, Ray, NVIDIA Triton, NVIDIA Dynamo, Distributed Systems, Software Defined Networking, Docker, Kubernetes, Python, APIs, Cloud Infrastructure, Tableau, Grafana, MCP\n\nAbout The Role\n\nWe are looking for a full-stack ML systems engineer. This is a SENIOR position and you will to work alongside the Chief Architect and the CEO to turn ML systems research into a product that developers and enterprises enjoy using.\n\nYou are a good fit if:\n\n* You have 5+ years of professional software engineering experience.\n* You have developed multi-agentic systems using multiple tool stacks e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel, or custom agent systems.\n* PLUS: You have deployed multi-agentic systems into live production\n* You have used model-serving platforms e.g., vLLM, SGLang, Ray, NVIDIA Dynamo\n* You have strong full-stack development skills. Especially front-end, including visualization via Tableau, Grafana etc.\n* You have used and developed-upon open source software\n* PLUS:You have contributed to open-source software\n* You have good product instincts: you can take a powerful backend capability and make it legible, useful, and satisfying for developers.\n* PLUS: You have worked as Solutions Architect or a Forward Deployment Engineer\n* You have experience with APIs, distributed systems, async jobs, queues, containers, deployment systems, or cloud infrastructure.\n* You are self-driven and can thrive in ill-defined, ambiguous, dynamic, early-stage work.\n* You possess clear written communication. You will help turn research-grade ideas into docs, examples, onboarding flows, and product language.\n\nWork experience\n\nHas hands- on experience with agentic systems - built multi- agent applications using LangChain, LangGraph, ADK, etc. ; understands agent scaling\n\nHard skills\n\nFull- stack development in Python\n\nLangChain, LangGraph, ADK, CrewAI, AutoGen, or equivalent.\n\nBaseline\n\nSeniority\n\n5+ years of experience 5+ years in ML systems engineering in production (academic years can substitute if PhD from top institution in relevant ML systems field)\n\nWork experience\n\nHas seen and dealt with scale, either on the orchestration side (what agents need to scale) or the infrastructure side (how to actually scale AI compute).\n\n*Nice-to-have*\n\nWork experience\n\nWorked at agent dev or inference provider companies\n\nBuilt products sold to enterprise buyers (CTO/CIO)\n\nExperience with products that have an open- source core + managed layer on top\n\nStartup or fast- paced environment experience\n\n*Education *\n\nPhD or MS from strong program in ML systems substitutes for experience\n\n*Hard skills*\n\nDistributed systems, Ray, or software- defined networking knowledge\n\nFamiliarity with vLLM, SGLang, Nvidia Triton, or equivalent\n\nExperience with containers, cloud infra, and deployment systems\n\nOpen- source contributions or development experience\n\nRole requirements\n\nSeniority\n\n5+ years of experience 5+ years in ML systems engineering in production (academic years can substitute if PhD from top institution in relevant ML systems field)\n\nWork experience\n\nHas seen and dealt with scale, either on the orchestration side (what agents need to scale) or the infrastructure side (how to actually scale AI compute).\n\nWorked at agent dev or inference provider companies\n\nBuilt products sold to enterprise buyers (CTO/CIO)\n\nExperience with products that have an open- source core + managed layer on top\n\nStartup or fast- paced environment experience\n\nEducation\n\nPhD or MS from strong program in ML systems substitutes for experience\n\nHard skills\n\nDistributed systems, Ray, or software- defined networking knowledge\n\nFamiliarity with vLLM, SGLang, Nvidia Triton, or equivalent\n\nExperience with containers, cloud infra, and deployment systems\n\nOpen- source contributions or development experience\n\nPay: $150,000.00 - $250,000.00 per year\n\nWork Location: In person","company":"Vaserjob","rawCompany":"vaserjob","city":"Alameda","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-09-09T08:20:40.418Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1211.00","title":"Computer Systems Analysts","slug":"computer-systems-analysts"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer (Systems)","description":"Salary: $150k to $250k\n\nEquity: Up to 1% equity\n\nOn-site work policy\n\nSunnyvale, CA onsite with some flexibility on a case-by-case basis.\n\nFull-time position\n\nLocation\n\nSaratoga, California, San Francisco Bay Area, California\n\nVisa sponsorship details\n\nOpen to visa transfers (e.g. OPT, H1B transfers)\n\nAdditional visa sponsorship details\n\nH1B transfers, new H1B applications, TN visas\n\nUs citizen and permanent residents\n\n5+ years of experience\n\n5+ years in ML systems engineering in production (academic years can substitute if PhD from top institution in relevant ML systems field)\n\nTech stack\n\nLangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, Google ADK, vLLM, SGLang, Ray, NVIDIA Triton, NVIDIA Dynamo, Distributed Systems, Software Defined Networking, Docker, Kubernetes, Python, APIs, Cloud Infrastructure, Tableau, Grafana, MCP\n\nAbout The Role\n\nWe are looking for a full-stack ML systems engineer. This is a SENIOR position and you will to work alongside the Chief Architect and the CEO to turn ML systems research into a product that developers and enterprises enjoy using.\n\nYou are a good fit if:\n\n* You have 5+ years of professional software engineering experience.\n* You have developed multi-agentic systems using multiple tool stacks e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel, or custom agent systems.\n* PLUS: You have deployed multi-agentic systems into live production\n* You have used model-serving platforms e.g., vLLM, SGLang, Ray, NVIDIA Dynamo\n* You have strong full-stack development skills. Especially front-end, including visualization via Tableau, Grafana etc.\n* You have used and developed-upon open source software\n* PLUS:You have contributed to open-source software\n* You have good product instincts: you can take a powerful backend capability and make it legible, useful, and satisfying for developers.\n* PLUS: You have worked as Solutions Architect or a Forward Deployment Engineer\n* You have experience with APIs, distributed systems, async jobs, queues, containers, deployment systems, or cloud infrastructure.\n* You are self-driven and can thrive in ill-defined, ambiguous, dynamic, early-stage work.\n* You possess clear written communication. You will help turn research-grade ideas into docs, examples, onboarding flows, and product language.\n\nWork experience\n\nHas hands- on experience with agentic systems - built multi- agent applications using LangChain, LangGraph, ADK, etc. ; understands agent scaling\n\nHard skills\n\nFull- stack development in Python\n\nLangChain, LangGraph, ADK, CrewAI, AutoGen, or equivalent.\n\nBaseline\n\nSeniority\n\n5+ years of experience 5+ years in ML systems engineering in production (academic years can substitute if PhD from top institution in relevant ML systems field)\n\nWork experience\n\nHas seen and dealt with scale, either on the orchestration side (what agents need to scale) or the infrastructure side (how to actually scale AI compute).\n\n*Nice-to-have*\n\nWork experience\n\nWorked at agent dev or inference provider companies\n\nBuilt products sold to enterprise buyers (CTO/CIO)\n\nExperience with products that have an open- source core + managed layer on top\n\nStartup or fast- paced environment experience\n\n*Education *\n\nPhD or MS from strong program in ML systems substitutes for experience\n\n*Hard skills*\n\nDistributed systems, Ray, or software- defined networking knowledge\n\nFamiliarity with vLLM, SGLang, Nvidia Triton, or equivalent\n\nExperience with containers, cloud infra, and deployment systems\n\nOpen- source contributions or development experience\n\nRole requirements\n\nSeniority\n\n5+ years of experience 5+ years in ML systems engineering in production (academic years can substitute if PhD from top institution in relevant ML systems field)\n\nWork experience\n\nHas seen and dealt with scale, either on the orchestration side (what agents need to scale) or the infrastructure side (how to actually scale AI compute).\n\nWorked at agent dev or inference provider companies\n\nBuilt products sold to enterprise buyers (CTO/CIO)\n\nExperience with products that have an open- source core + managed layer on top\n\nStartup or fast- paced environment experience\n\nEducation\n\nPhD or MS from strong program in ML systems substitutes for experience\n\nHard skills\n\nDistributed systems, Ray, or software- defined networking knowledge\n\nFamiliarity with vLLM, SGLang, Nvidia Triton, or equivalent\n\nExperience with containers, cloud infra, and deployment systems\n\nOpen- source contributions or development experience\n\nPay: $150,000.00 - $250,000.00 per year\n\nWork Location: In person","datePosted":"2026-09-09T08:20:40.418Z","dateModified":"2026-09-09T08:20:40.418Z","hiringOrganization":{"@type":"Organization","name":"Vaserjob","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Alameda","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"8bbc6a2c52ecb98a103faced"},"url":"https://jobsearcher.com/jobs/8bbc6a2c52ecb98a103faced"}}