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LiveKit

Open-source WebRTC platform with managed cloud

Research Engineer - Reinforcement Learning

AI ResearchUpdated on Nov 10
Full-timeRemote

About the Job

Requirements

  • Strong Python engineering skills.
  • Experience carrying a model from raw data through production.
  • Ability to assess data coverage, diversity, and leakage.
  • Ability to anticipate weak reward exploitation and design against it.
  • Comfort working with GPUs and understanding their limitations.
  • Ability to determine when model training is appropriate.
  • Ability to work collaboratively in a remote environment.

Responsibilities

  • Build the environments and verifiers used to train models.
  • Own the synthetic data pipeline, from generation through quality gates.
  • Run training experiments end to end and explain what changed the model.
  • Build the evaluations a release must pass.
  • Choose and adapt open-weight base models for assigned tasks.
  • Ensure trained behavior performs effectively for voice and text agents.
  • Ship models into production and improve them using real-world usage.

Desired Qualifications

  • Experience with post-training, including fine-tuning, reward design, or reinforcement learning such as GRPO.
  • Experience with RL and fine-tuning frameworks such as TRL, verl, or OpenRLHF, or a self-written training loop.
  • Experience with fast rollouts using vLLM or SGLang and multi-GPU training with FSDP.
  • Experience training tool-using or multi-turn agents.
  • Experience with execution sandboxes, verifiers, evaluation harnesses, or tooling used by other engineers.
  • Experience with open-weight model families such as Qwen or Llama, and LoRA or similar techniques.

About the Company

LiveKit

Open-source WebRTC platform with managed cloud

LiveKit provides an open-source platform for building real-time audio and video applications using a complete WebRTC stack. Developers can integrate live media with LiveKit’s APIs and SDKs, either by self-hosting the open-source software or by using LiveKit Cloud, a fully-managed cloud service with a globally distributed network. This setup handles media infrastructure at scale, allowing apps to support large user bases without managing servers themselves. The goal is to help developers add real-time communication features and scale their apps globally with flexible deployment options.

Company size
51-200
Company stage
Series C
Total funding
$181.2M
Headquarters
San Jose, CA
Founded
2021

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