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Responsibilities:
- Deploying models to production: Take LLMs and put them into production across one or more machines on GPU infrastructure.
- Serving frameworks: Stand up and operate serving infrastructure using vLLM, SGLang, or TensorRT-LLM.
- Optimizing for scale: Apply quantization, batching, caching, and routing to keep latency and cost in check.
Requirements:
- Production LLM serving experience with vLLM, SGLang, or TensorRT-LLM.
- Hands-on inference optimization with quantization, batching, caching, and routing.
- Strong engineering skills in Python or Golang with real production code.
Culture & Values:
- Make it Happen: Relentless bias for action and grit to push through obstacles.
- Own the Outcome: Responsibility ends when value is delivered, connecting daily actions to broader success.
- Create Wow: Measure success by the experience generated for customers and team.
vCluster Labs
vCluster Labs is a venture-backed tech startup pioneering Kubernetes virtualization for the AI era, enabling AI Cloud providers and AI factories to operate GPU infrastructure with hyperscaler-like experiences. We raised over $30M from top-tier VCs like Khosla Ventures, are in a hyper-growth phase, and maintain a remote-first, distributed global team with headquarters in San Francisco.