Software Engineer, Infrastructure
Mountain View, CAFull-timePosted 6mo agoStill listed 4 days ago
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Job overview
Scaled Cognition is hiring a Software Engineer, Infrastructure. Scaled Cognition is a model lab focused on customer experience, pioneering agentic models for reliable enterprise applications. Backed by Khosla Ventures, their Agentic Pretrained Transformer (APT) aims to eliminate hallucinations and increase reliability in CX workflows. The company, founded by serial AI entrepreneurs and built by world-class researchers, advances agentic AI for safe, policy-aligned automation.
Key focus areas include Design and improve inference infrastructure that powers AI models, Benchmark, profile, monitor and analyze latency and throughput, and Drive improvements throughout the stack.
Successful candidates bring Cloud Deployment Experience and GPU Infrastructure Design Experience. Important skills include AWS, GCP, Azure, Designing GPU Infrastructure, Implementing GPU Tooling, and Scalability. Preferred (not required): Design Inference Infrastructure, Benchmark, Profile, and Azure Monitor.
Skills & qualifications
Skills
Qualifications
Full job description
Scaled Cognition is the world’s only model lab dedicated exclusively to customer experience and pioneering agentic models purpose-built for reliable action-taking enterprise applications. Backed by Khosla Ventures, the company’s flagship Agentic Pretrained Transformer (APT) eliminates hallucinations, enforces enterprise policies and increases reliability in real-world CX workflows. Founded by serial AI entrepreneurs, former Microsoft Corporate Vice President of Conversational AI Dan Roth, and UC Berkeley AI Professor Dan Klein, and built by a team of world-class PhD researchers and engineers, Scaled Cognition advances the science of agentic AI to deliver safe, policy-aligned automation that enterprises can trust.
As a Software Engineer, Infrastructure at Scaled Cognition you will:
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Design and improve inference infrastructure that powers our AI models.
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Benchmark, profile, monitor and analyze latency and throughput and drive improvements throughout the stack.
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Collaborate with research scientists and product engineers to streamline the end-to-end process from model development to production deployment.
You might be the right person for the job if you:
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Are a continuous learner and are eager to explore new tools and technologies.
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Thrive in a dynamic environment and are comfortable adapting to changing priorities while maintaining a focus on delivering high-quality solutions.
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Have successfully navigated projects with significant product and technical ambiguity, and you excel at the intersection of complex technical challenges and user-focused solutions.
Key Qualifications:
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Experience deploying systems on major cloud platforms (AWS, GCP, Azure).
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Prior experience designing and implementing GPU infrastructure / tooling.
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A strong sense for scalability and developing secure, highly reliable environments.
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