Scale Ai - San Francisco, CA
posted 3 months ago
Scale's Generative AI Data Engine powers the most advanced LLMs and generative models in the world through world-class RLHF/RLAIF, data generation, model evaluation, safety, and alignment. As the Manager of the Generative AI team, you will be responsible for managing and leading a group of talented researchers and engineers. Your primary focus will be to leverage your expertise in LLMs, generative models, and other foundational models to create and execute an AI roadmap which will help Scale accelerate our customers' Generative AI initiatives forward. This is an exciting opportunity to work on cutting-edge technologies and collaborate with industry-leading professionals. We are building a large hybrid human-machine system in service of ML pipelines for dozens of industry-leading customers. We currently complete millions of tasks a month and will grow to complete billions monthly. You will manage a team of highly effective researchers and engineers, providing guidance, mentorship, and technical leadership to a team working on Generative AI projects. You will develop and evaluate methods for integrating machine learning into human-in-the-loop labeling systems to ensure high-quality and throughput labels for our customers. Additionally, you will implement and improve on state-of-the-art models developed internally and from the community, putting them into production to solve problems for our customers and taskers. Collaboration with product and research teams will be essential to identify opportunities for improvement in our current product line and for enabling upcoming product lines. You will work with massive datasets to develop both generic models as well as fine-tune models for specific products, and engage with customers and third-party research groups to understand their goals and define how we can enable them. Building a scalable ML platform to automate our ML services, including automated model retraining and evaluation, will also be a key responsibility. You must be able and willing to multi-task and learn new technologies quickly, and be prepared to commute to the San Francisco Office 1-2 times weekly.