scaled-cognition

Software Engineer, Infrastructure

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  • onsite
  • FullTime
  • Engineering
  • New York
  • New York
Work arrangement
onsite
Employment
FullTime
Stated compensation
Not specified
Stated sponsorship
Not stated
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Requirements

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Remote policy
onsite
“Provider workplace type: onsite”
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Employment type
FullTime
9 fields not stated in this posting
Employer sponsorship
Not specified
Geographic scope
Not specified
Degree requirement
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Security clearance
Not mentioned
Timezone / hours
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Citizenship requirement
Not mentioned
Minimum experience (years)
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Original job description

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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: 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. 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: Are a continuous learner and are eager to explore new tools and technologies. Thrive in a dynamic environment and are comfortable adapting to changing priorities while maintaining a focus on delivering high-quality solutions. 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: Experience deploying systems on major cloud platforms (AWS, GCP, Azure). Prior experience designing and implementing GPU infrastructure / tooling. A strong sense for scalability and developing secure, highly reliable environments.
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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:

  • Design and improve inference infrastructure that powers our AI models.

  • Benchmark, profile, monitor and analyze latency and throughput and drive improvements throughout the stack.

  • 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:

  • Are a continuous learner and are eager to explore new tools and technologies.

  • Thrive in a dynamic environment and are comfortable adapting to changing priorities while maintaining a focus on delivering high-quality solutions.

  • 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:

  • Experience deploying systems on major cloud platforms (AWS, GCP, Azure).

  • Prior experience designing and implementing GPU infrastructure / tooling.

  • A strong sense for scalability and developing secure, highly reliable environments.

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