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LM Studio

Runs local LLMs on personal computer

Software Engineer - Agent Harness

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USAIn-person

About the Job

Requirements

  • Significant experience building production software involving language models, developer tools, or automation.
  • Strong understanding of tool calling, structured model output, context construction, and streaming inference.
  • Experience building stateful systems that perform multi-step work and recover cleanly from failures.
  • Excellent TypeScript and general software engineering fundamentals.
  • Deep interest in open models and a practical understanding of their strengths and limitations.

Responsibilities

  • Build and improve the agent harness that powers Bionic.
  • Make local and cloud models reliable at using files, search, Git, the shell, web tools, and document tools.
  • Integrate new open models and optimize how they perform in the Bionic agent harness.
  • Manage conversation history, working context, tool results, interruptions, and recovery.
  • Build repeatable evaluations and diagnostics for understanding where and why an agent fails.
  • Constrain the model in a smart way so it remains useful.
  • Work across Bionic, the LM Studio runtime, and LM Studio cloud to improve the complete system.

About the Company

LM Studio

Runs local LLMs on personal computer

LM Studio provides a local-first AI platform that lets users download, install, and run large language models directly on their own computers, avoiding cloud services. It supports multiple LLM frameworks and offers an easy interface for configuration and customization, so users can tailor models for tasks like natural language processing, text generation, and data analysis. By running models locally, LM Studio keeps data on the user’s device, giving them greater privacy and control while removing reliance on external servers. This makes LM Studio different from many competitors that require cloud access or single-framework support, as it emphasizes local execution, privacy, and broad compatibility. The goal is to help developers, researchers, and enthusiasts use AI tools securely and efficiently, integrating local LLMs into their workflows and projects.

Company size
11-50
Company stage
Early VC
Total funding
$19.3M
Headquarters
New York City, New York
Founded
2023

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