RLAIF Jobs

Together AI

The Turbo Research team focuses on making post-training and reinforcement learning for large language models efficient, scalable, and reliable. This work intersects RL algorithms, inference systems, and large-scale experimentation, where inference costs significantly impact training efficiency and the practicality of learning algorithms. As a research intern, you will investigate RL and post-training methods whose performance and scalability are closely tied to inference behavior, co-designing algorithms and systems. Projects aim to enable new experimental regimes, including larger models, longer rollouts, and more complex evaluations, by re-evaluating the interaction between inference, scheduling, and training.

Together AI

The Turbo team operates at the intersection of efficient inference (algorithms, architectures, engines) and post-training/RL systems. We are responsible for building and managing the systems that power Together's API, focusing on high-performance inference and RL/post-training engines capable of operating at production scale. Our core mission is to advance the frontiers of efficient inference and RL-driven training, aiming to make models significantly faster and more cost-effective to run, while simultaneously enhancing their capabilities through RL-based post-training methods. This role involves working across the entire stack, from RL algorithms and training engines to kernels and serving systems, to develop and refine state-of-the-art models using RL pipelines. We value individuals with deep expertise in one area and a strong willingness to collaborate and grow across others.

$200k - $280k