Member of Technical Staff - Quantitative Research

<h2><strong>About Uncharted/Udio</strong></h2> <p>Udio builds extraordinary AI experiences to empower musical artists and super fans. Pairing best-in-class AI models with groundbreaking partnerships across the music industry, Udio's mission is to champion musicians and expand how fans engage with their favorite music and artists. Udio is backed by leading lights from tech and music, including a16z, Redpoint, Hanwha, will.i.am, Steve Stoute, Kevin Wall, and many others. For more information, please visit <a href="http://udio.com">udio.com</a>.</p> <h2><strong>About the Role</strong></h2> <p>We are looking for a full-stack scientist to pioneer quantitative research efforts at Udio.</p> <p>You will build at the intersection of research, engineering and product, bridging disciplines by drawing on huge, one-of-a-kind proprietary datasets of music, metadata and user interactions/feedback. Working closely with the modeling team, product leadership and the music evaluation manager, you will apply your research toward pushing the frontier of music generation, setting a course through a bleeding-edge product category and unlocking new revenues for artists and experiences for fans.</p> <h2><strong>What You’ll Do</strong></h2> <p><strong>Design own evaluation/optimization frameworks for frontier music models</strong></p> <p>You’ll dive deep under the hood of our music generation systems, applying computational human resources to understand model capabilities and identify areas for growth. You’ll build optimization loops and apply your findings to our pretraining, post-training and inference systems as applicable.</p> <p><strong>Drive product research roadmap</strong></p> <p>You’ll own our data roadmap end-to-end, formulating research questions, exploring/linking/expanding data sources and conducting experiments at your discretion. Your work will span data mining, machine learning, causal inference, survey design and more, and your results will be critical for decision-making in product development, research investment and overall business direction.</p> <p><strong>Build stable infrastructure</strong></p> <p>Your work will reach far beyond the jupyter kernel, manifesting in robust integrations with our research product tech stacks, potentially in performance-critical paths. You’ll also build large-scale standalone data processing systems, allocating resources as needed to manage the data ecosystem.</p> <p><strong>Champion scientific rigor</strong></p> <p>As our first quantitative researcher, you’ll cultivate a culture of scientific rigor across the company and deepen common understanding of models, users and data. You’ll proactively identify opportunities, define metrics, share results, and build a rigorous foundation upon which to understand our highly subjective domain.</p> <p> </p> <h2><strong>What We’re Looking For</strong></h2> <ul> <li><strong>Deep quantitative expertise:</strong> Ph.D. in statistics, mathematics, physics, or another quantitative discipline, or 5+ years’ industry experience as a quantitative analyst / data scientist</li> <li><strong>Autonomy ownership: </strong>You thrive in greenfield research domains, undefined product categories and small, flat teams. Driven by curiosity and good taste, you ask good questions in addition to finding good answers.</li> <li><strong>Engineering chops: </strong>You’re adept in translating your ideas into clear, production-ready code and collaborating in an active research codebase.</li> <li><strong>Excellence in scientific communication: </strong>You relate technical information with rigor and crystal clarity to researchers, engineers, product managers and business partners alike.</li> </ul> <p> </p> <h2><strong>Nice to Have</strong></h2> <ul> <li><strong>Obsession with music the science of sound. </strong>Experience in DSP, MIR, music production / composition / performance, and a big record collection all a huge plus.</li> <li><strong>Familiarity</strong> <strong>with deep learning fr ... (truncated, view full listing at source)