Research Engineer, Large-Scale Training

<h3><span style="font-family: helvetica, arial, sans-serif;">About the Role</span></h3> <p class="isSelectedEnd"><span style="font-family: helvetica, arial, sans-serif;">The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems.</span></p> <p class="isSelectedEnd"><span style="font-family: helvetica, arial, sans-serif;">As a Research Engineer on the Scaling Team within Model Shaping, you will turn cutting-edge research on efficient foundation model training into robust, high-performance systems. You will profile and optimize Together's training infrastructure, identify performance bottlenecks across the stack, and implement state-of-the-art techniques from both the research literature and our own scientists in production environments.</span></p> <p class="isSelectedEnd"><span style="font-family: helvetica, arial, sans-serif;">Your work will directly shape the fine-tuning experience of Together's customers. You will rapidly bring newly released open-source models onto the Model Shaping platform, ensuring they train efficiently and reliably across diverse customer workloads. Working closely with Research Scientists, you will also build the experimental infrastructure that accelerates research and enables validated ideas to be deployed reliably at scale.</span></p> <h3><span style="font-family: helvetica, arial, sans-serif;">Responsibilities</span></h3> <ul data-spread="false"> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Design, implement, and optimize core components