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 RoleWe 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 DoBuild 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
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
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
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 [email protected].
Skills Required
- Strong Python engineering skills
- Experience carrying a model from raw data through production
- Ability to design high-quality data pipelines with coverage, diversity, and leakage controls
- Ability to design against reward hacking and weak reward functions
- Comfort working with GPUs and understanding their limitations
- Ability to determine when model training is appropriate
- Ability to collaborate effectively in a remote environment
- Post-training experience, including fine-tuning, reward design, or reinforcement learning such as GRPO
- Experience with TRL, verl, OpenRLHF, or custom training loops
- Experience with vLLM, SGLang, or FSDP
- Experience training tool-using or multi-turn agents
- Experience with execution sandboxes, verifiers, evaluation harnesses, or shared developer tooling
- Experience with open-weight models such as Qwen or Llama and LoRA
What We Do
LiveKit's network is optimized for ultra-low latency, extreme resiliency, and massive scale.
