riverai · Palo Alto, CA
At River, our mission is to create personal AI owned and shaped by each individual. To achieve this, we are rewriting the entire stack from scratch: personal hardware for local inference, bespoke training infrastructure, next-generation UIs, and frontier deep learning research. Who we are We are scientists, engineers, and builders from the industry's top tech companies and AI labs. We bring a proven track record of scaling consumer systems for hundreds of millions of users and architecting the pre-training infrastructure behind today's frontier models. About the Role We are looking for exceptional applied researchers to work directly with customers across industries to train and improve their own models. Your goal is to translate real-world problems, domain expertise, and customer data into models that deliver measurable value in their workflows. You will own the applied research lifecycle, from defining the problem and preparing data to designing experiments, training models, and evaluating results. Working closely with customer teams and River's research and infrastructure teams, you will apply and adapt modern deep learning techniques to solve practical problems and help customers bring their models into production. What You’ll Do Partner directly with customers across industries to understand their workflows, identify high-value modeling problems, and define success criteria. Develop data preparation and curation pipelines with customer teams, turning domain-specific data and expert feedback into training datasets and representative evaluations. Design and run training experiments using techniques such as continued pre-training, supervised fine-tuning, reinforcement learning, and parameter-efficient fine-tuning (PEFT), selecting approaches that fit each customer's goals, data, and compute budget. Build evaluation suites, analyze model failures, and iterate on data and training methods to improve quality, reliability, and performance on real customer tasks. Work…
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