Teams at LiveKit

Build post-training infrastructure for voice and text agents, including training environments, verifiers, synthetic data pipelines, evaluations, and model release gates. Run end-to-end training experiments, select open-weight models, improve tool-using and multi-turn behavior, deploy models to production, and iterate using real-world usage. The role emphasizes Python engineering, reinforcement learning, GPU-based training, data quality, reward design, and production machine learning.

Design, implement, and manage LiveKit's infrastructure, focusing on performance, reliability, and automation while ensuring effective incident management and coordination with vendors.

As a Senior Product Engineer, you'll build user-facing products on the LiveKit platform in TypeScript and Go while engaging with developers and contributing to strategic decisions.