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≈ $130k – $281k per year (Estimated)
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In office (New York)
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Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Jan 29, 2026. Scaled Cognition scores B on the Alion truth index.

Overview
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Impact
Profile match
The only frontier model for CX that eliminates hallucinations. APT-1 delivers Super-Reliable Intelligence—agents that follow policy, execute actions, and perform at scale.

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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