Senior Machine Learning Systems Engineer (AI Agents & Distributed Infrastructure)

🚀 Senior ML Engineer (Systems) | AI Agents & Distributed Systems

Location: Sunnyvale, CA — On-site

Employment Type: Full-time

Experience: 5+ years

Compensation: $150K–$230K + up to 1% equity

Visa: H-1B transfers, new H-1B applications & TN visas supported

We’re hiring a Senior ML Engineer (Systems) to join an early-stage AI company building infrastructure for the next generation of multi-agent enterprise workflows.

This is a highly hands-on role for an engineer who can bridge ML systems research, agentic AI, distributed infrastructure, full-stack development, and product engineering.

You’ll work closely with the CEO and Chief Architect to turn research-grade ML systems ideas into products that developers and enterprise customers genuinely enjoy using.

🔥 What You’ll Do

• Build and productionize multi-agentic AI systems
• Design scalable agent orchestration and infrastructure
• Develop full-stack applications primarily using Python
• Work with agent frameworks such as LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, Google ADK, or equivalent
• Deploy and optimize model-serving infrastructure using technologies such as vLLM, SGLang, Ray, NVIDIA Triton, or NVIDIA Dynamo
• Build systems involving APIs, distributed systems, asynchronous jobs, queues, containers, deployment platforms, and cloud infrastructure
• Develop intuitive developer-facing products around complex ML infrastructure
• Create visualizations and product experiences using tools such as Tableau and Grafana
• Work extensively with open-source software, with opportunities to contribute upstream
• Translate research-grade concepts into documentation, examples, onboarding experiences, and product language
• Collaborate directly with technical leadership in an ambiguous, fast-moving startup environment
• Help shape architecture, engineering practices, and the product itself

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🧠 Ideal Candidate

You’ll be a strong fit if you have:

(academic years can substitute if PhD from top institution in relevant ML systems field)

• 5+ years of professional software engineering experience
• 5+ years of ML systems engineering experience in production
• Strong experience building multi-agent systems
• Experience deploying multi-agent systems into live production environments
• Strong understanding of agent scaling, distributed systems, or AI infrastructure
• Hands-on experience with one or more agent frameworks:
• LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, Google ADK, or custom agent frameworks
• Experience with model-serving platforms such as vLLM, SGLang, Ray, NVIDIA Triton, or NVIDIA Dynamo
• Strong full-stack engineering capabilities
• Experience with containers, cloud infrastructure, deployment systems, APIs, async jobs, queues, and distributed systems
• Experience developing with open-source software
• Strong product instincts and the ability to make sophisticated backend capabilities understandable and useful to developers
• Excellent written communication skills
• Ability to operate independently in an early-stage, ambiguous, rapidly changing environment

⭐ Strong Plus

Candidates with any of the following will stand out:

• Experience as a Solutions Architect

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• Experience as a Forward Deployed Engineer
• Contributions to open-source projects
• Experience working at an AI agent development company or inference provider
• Experience building products sold to enterprise CTO/CIO buyers
• Experience with products combining an open-source core + managed cloud/service layer
• Experience scaling AI compute or agent orchestration systems
• Experience in startup or high-growth technical environments
• PhD or MS in ML Systems / Computer Science / a closely related field from a strong program

🛠️ Technology Environment

AI / Agentic Systems:

LangGraph • LangChain • AutoGen • CrewAI • Semantic Kernel • Google ADK • MCP

ML Infrastructure:

vLLM • SGLang • Ray • NVIDIA Triton • NVIDIA Dynamo

Systems & Infrastructure:

Distributed Systems • Software-Defined Networking • Docker • Kubernetes • Cloud Infrastructure • Deployment Systems • APIs • Async Jobs • Queues

Engineering:

Python • Full-Stack Development • Open Source

Observability / Visualization:

Tableau • Grafana

🚫 This Role Is NOT a Good Fit If You Are:

• Primarily from a traditional enterprise/non-technical background
• Focused only on the application layer without systems, scaling, or infrastructure experience
• Looking for a role where you are primarily managing rather than coding and building hands-on

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• Too far removed from day-to-day technical implementation

🎓 Education / Experience Flexibility

Professional experience is highly valued. A PhD or MS from a top institution in a relevant ML systems field may substitute for some professional experience.

📍 Work Arrangement

On-site in Sunnyvale, California, with limited flexibility considered on a case-by-case basis.

💰 Compensation & Benefits

Base Salary: $150,000–$230,000

Equity: Up to 1%

Position: Full-time

Hiring: 1–2 engineers

🛂 Visa Support

The company is open to:

• H-1B transfers
• New H-1B applications
• TN visas
• OPT / eligible visa transfers

🌟 Why This Opportunity?

This is an opportunity to work at the intersection of agentic AI, ML infrastructure, distributed systems, and enterprise software at an early-stage company.

You won’t simply maintain an existing platform—you’ll help design, build, scale, and productize the systems that power the next generation of enterprise AI workflows.

If you’re an engineer who enjoys going deep technically, working directly with technical leadership, solving ambiguous systems problems, and turning cutting-edge AI research into production software, we’d love to hear from you.

📩 Apply directly or message me with your resume/profile.

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