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Applied Compute

Custom AI models and enterprise agents

Research Systems Engineer

AI ResearchConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • Experience training or serving large language models.
  • Experience building reinforcement learning environments and evaluations for language models.
  • Proficiency in PyTorch, JAX, or similar machine learning frameworks, with experience in distributed training.
  • Strong experimental design skills, including the ability to set up experiments that answer research questions.

Responsibilities

  • Post-train frontier-scale language models on enterprise tasks and environments.
  • Explore and develop reinforcement learning techniques by co-designing algorithms and systems.
  • Build high-performance internal tools for probing, debugging, and analyzing training runs.
  • Partner with infrastructure engineers to scale training and inference efficiently.

Desired Qualifications

  • Background in pre-training or post-training research.
  • Previous experience in high-performance computing environments or large-scale clusters.
  • Contributions to open-source machine learning research or infrastructure.
  • Demonstrated technical creativity through published research, open-source contributions, or side projects.

About the Company

Applied Compute

Custom AI models and enterprise agents

Applied Compute creates customized AI capabilities for enterprises by building proprietary AI models and in-house AI agents, a concept they call Specific Intelligence. Its products train on a company’s own data and are fine-tuned for specific workflows, delivered via a vertically integrated platform that includes training infrastructure, an agent platform, and developer tools on a GPU cluster, with engineers embedded inside customer teams to accelerate deployment. The company differentiates itself by focusing on proprietary data, maintaining its own tech stack, and embedding its engineers with customers to deliver deeply integrated solutions that are hard for competitors to copy. Its goal is to give enterprises a competitive edge by deploying production-ready AI agents and models that fit seamlessly into business operations and processes.

Company size
11-50
Company stage
Series C
Total funding
$510M
Headquarters
San Francisco, CA
Founded
2025

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