Multimodal understanding: build vision-language systems that let Descript's agentic editing features reason over the visual and audio content of a project.

Evaluation: design the benchmarks and evals that make editorial quality measurable, and that balance quality against cost and latency.

Data: build the datasets your work depends on, including synthetic data generation where real examples don't exist at scale.

Training: train specialized models from scratch or fine-tune existing foundation models, whichever gets the capability we need.

Shipping: take models from prototype to production with the agent and engineering teams.

Direction-setting: identify the next research direction that should become a Descript feature, not just a paper. More senior candidates should expect to own this directly; more junior candidates will grow into it.

Publishing: take your work to academic venues if you'd like. We support it, but it isn't a requirement of the role.

Proven ability to design and implement deep learning algorithms, demonstrated by publications, open-source work, or models you've shipped.

Strong programming skills and deep fluency in PyTorch.

A track record of generating new ideas in machine learning. You produce more ideas than you can implement, and once an experiment setup is established, you can run and evaluate many of them quickly rather than being bottlenecked on infrastructure.

Strong experimental judgment. You test ideas fast, and you're honest with yourself and the team about which ones don't pan out.

Clear written and verbal communication, including when a direction isn't working, so the team doesn't waste time following a lead that's already dead.

Applied Research Scientist, AI Research

Responsibilities

Qualification

Required

Benefits

Company

Descript

More roles at Descript