Nuance Research Fellow
Nuance Labs
| Company | Nuance Labs |
| Category | Science & Research |
| Location | Seattle |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 11 Jun 2026 |
| Last verified | 9 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
About Nuance Labs
Nuance Labs is building photorealistic, real-time AI avatars with emotional intelligence: a full-duplex audiovisual system that can listen, speak, react, interrupt, and respond like a real person.
We're a research company, with PhDs from MIT, UW, Oxford, CMU, and Johns Hopkins, and industry experience from Apple, Meta, Amazon AGI, and Discord. The team is small, the work is real, and the problems are unsolved.
How Nuance Differentiates
Most conversational AI avatars today are hacks — a face slapped on a speech-to-speech pipeline, stuck in the uncanny valley: emotionless, mechanical, one-turn-at-a-time. Current systems take 2–5 seconds to respond; natural conversation requires sub-500ms. That's a 10x improvement, and it demands rethinking the entire stack.
That rethinking starts with full-duplex: an AI that listens and speaks simultaneously, perceives emotion in real time, and responds with a face that actually reflects it. It's an extremely hard problem, and we're developing foundation models designed for it from the ground up. About the Role
The Nuance Research Fellowship is a 3-month engagement for early-career researchers who want to work at the frontier of Multimodal LLMs , generative modeling, and real-time audiovisual AI. The program is open to current PhD students (on internship, leave, or in their final stretch) and recent graduates from BS, MS, or PhD programs.
As a fellow, you’ll own a real research problem inside one of our core workstreams: pretraining, post-training, RL, evaluation, data, multimodal modeling, generative modeling, or inference. Depending on your strengths, this could mean training omni models from scratch, improving real-time audio-video-language reasoning, building evals for full-duplex interaction, or exploring model families such as flow matching and diffusion for controllable, high-fidelity generation.
This is designed as a mutual trial for a long-term role at Nuance, not a short standalone internship. At the end of three months, we’ll decide together whether to convert to a full-time Member of Technical Staff role. Fellows who convert step into MTS-level scope and ownership from day one.
What You’ll Own
Own a concrete research problem from framing through experiments, analysis, and integration into the Nuance stack
Work on frontier Multimodal LLM systems spanning audio, video, language, and real-time interaction
Explore and adapt modern generative modeling techniques, including flow matching, diffusion, autoregressive modeling, and hybrid approaches where they fit
Read papers, reproduce key results, and turn promising ideas into production-grade experiments
Design, instrument, debug, and interpret training and evaluation runs with scientific rigor
Build evaluation harnesses, benchmarks, and analysis tooling for real-time conversational agents
Take research-grade prototypes and turn them into systems that ship
Work closely with senior researchers and engineers across the team; ramp on the stack fast
What We’re Looking For
Hard requirements:
Strong working knowledge of PyTorch and deep learning — you can train a model, debug a training run, and reason about what’s happening at the loss level
At least one first-author paper at a tier 1 venue (main conference proceedings) — NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP, NAACL, ICASSP, Interspeech, MLSys, SIGGRAPH, or equivalent — or equivalent evidence of unusually strong research taste and execution
Genuine interest in joining Nuance full-time after the fellowship. We are looking for long-term partners on this journey
Beyond the hard bar:
Currently enrolled in or recently completed a BS, MS, or PhD in CS, ML, math, physics, EE, or a related field
Strong programming ability and software engineering instincts
High agency — when you see something broken or slow, you fix it; when you see an opportunity, you take it before being asked
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