LiveKit
via Ashby
Research Engineer (Reinforcement Learning)
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 27d ago
The date the source published, not the day we noticed it (2026-08-18). Last seen at its source 1h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
North America, EMEA
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $160k–225k/yr
Middle 50% of 2271 listings that do state pay — Engineering · all levels · North America · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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ashby employer's own board first seen 27d ago · last seen 1h ago
The listing
About LiveKit
LiveKit is building the infrastructure layer for the voice-driven era of computing. Our platform gives developers everything they need to build, test, deploy, scale, and observe agents in production. 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.
About This Role
We are looking for an exceptional engineer to build post-training at LiveKit. 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.
What You'll Do
Build the environments and verifiers our models train against
Own the synthetic data pipeline, from generation through the quality gates
Run training experiments end to end, and explain what moved the model
Build the evaluations a release has to clear
Choose and adapt open-weight base models for our tasks
Make trained behavior hold up for voice and text agents alike
Ship models into production and keep improving them on real usage
Who You Are
A strong Python engineer
Have carried a model from raw data through to production
Treat data as the product: coverage, diversity, leakage
Assume a model will exploit a weak reward, and design against it
Comfortable with GPUs and honest about their limits
Know when to train, and when not to
Comfortable working collaboratively in a remote environment
Nice to Have
Experience with post-training: fine-tuning, reward design, or reinforcement learning such as GRPO
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
Our Commitment to You
The opportunity to shape the brand of a fast-growing developer platform
Collaboration with a small, senior team that deeply values craft and creativity
Competitive salary and equity package
Health, dental, and vision benefits
Flexible vacation policy
LiveKit is an equal opportunity employer and does not discriminate on the basis of any characteristic protected by applicable law. If you require a reasonable accommodation during the application or interview process, please contact recruiting@livekit.io.