LiveKit
Research Engineer (Reinforcement Learning)
North America
Sponsorship not specifiedDetected 65 days ago
PythonSalesforceResearchCollaboration
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About the role
- Our agents run over voice and increasingly over text channels like
- SMS and chat, and the interesting problems show up over long horizons:
- staying useful across many sessions, working with context that accumulates over time, and using tools reliably in the middle of a live conversation.
Responsibilities
- Build the environments and verifiers our models train against
- Own the synthetic data pipeline, from generation through the quality gates
- Build the evaluations a release has to clear
- Assume a model will exploit a weak reward, and design against it
- LiveKit is building the infrastructure layer for the voice-driven era of computing.
Nice to have
- RL and fine-tuning frameworks such as TRL, verl, or OpenRLHF, or a training loop you wrote yourself
- Fast rollouts with vLLM or SGLang, multi-GPU training with FSDP
- Training tool-using or multi-turn agents
- Execution sandboxes, verifiers, eval harnesses, or tooling other engineers depend on
- Open-weight families such as Qwen or Llama, LoRA and similar
- The opportunity to shape the brand of a fast-growing developer platform
- Collaboration with a small, senior team that deeply values craft and creativity
- LiveKit is an equal opportunity employer and does not discriminate on the basis of any characteristic protected by applicable law.
Compensation
- Competitive salary and equity package
Benefits
- Competitive salary and equity package
- Health, dental, and vision benefits
- Flexible vacation policy
- Treat data as the product: coverage, diversity, leakage
Company info
- Founded in 2021, LiveKit powers voice AI applications for OpenAI, xAI, Salesforce, Coursera, Spotify, and thousands of others, collectively facilitating billions of calls each year.
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This listing is sourced directly from LiveKit's careers page and normalized into a canonical job model.