Product Manager, AI Research

<p>Descript’s vision is to put video in every communicator’s toolkit. Back in the day you needed like six monitors and a bachelor’s degree to edit video. Descript lets you do it by editing docs &amp; slides, and increasingly by just asking AI. In the future, maybe you won’t even need to ask! But building a new way to record or generate (or both!) videos that look &amp; sound good comes with a series of unique design, technology, and business challenges. In other words, we need really good product managers.</p> <p>We’re looking for a Product Manager to help build the future of video editing with AI. You’ll work alongside a small, flat, highly collaborative team of experienced PMs, AI researchers, engineers, designers, and marketers. This is an opportunity to get hands-on experience with cutting-edge AI technology in a product users love and grow fast in your PM craft.</p> <p>We're looking for a Product Manager to lead the AI Research and Enablement roadmap at Descript. This role sits at the intersection of cutting-edge AI research, production ML infrastructure, and product strategy. You'll be responsible for ensuring our AI capabilities are best-in-class while enabling our product teams to ship AI-powered features that delight users.</p> <h1>Teams You'll Partner with</h1> <h2>AI Research</h2> <p>The AI Research team leverages, trains, and validates powerful models for our product use cases across two core areas:</p> <ul> <li><strong>Audio/Video Research</strong>: Models for understanding, augmenting, and generating audio/video content (transcription, lipsync, video regenerate, TTS, avatars, etc.).</li> <li><strong>LLM Research</strong>: Evaluating and optimizing LLMs for Descript products, co-designing agent architecture, experimenting with token optimizations and fine-tuning.</li> </ul> <h2>AI Enablement</h2> <p>The AI Enablement team supports integrating 1P and 3P models into the Descript product:</p> <ul> <li>Building and maintaining standardized 3P model integrations (LLM providers, generative model APIs).</li> <li>Productionizing 1P models for specific use-cases.</li> <li>MLOps infrastructure (evals framework, inference infra, training infra, data pipelines).</li> </ul> <h1>What You'll Do</h1> <h3>Strategic Prioritization</h3> <ul> <li><strong>Make build vs. buy decisions</strong>: Evaluate when to train our own models vs. integrate third-party solutions based on market gaps, competitive advantage, and ROI</li> <li><strong>Balance research investment</strong>: Allocate team resources between long-term research bets, feature work, and maintenance</li> <li><strong>Guide research direction</strong>: Use product insight to infor