Nuance Research Fellow

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 more. Backed by Accel, Lightspeed, South Park Commons, and NVIDIA, we combine frontier research with ruthless engineering needed for consumer-grade, real-time systems. 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

A bias toward shipping over polishing, with the judgment to know when each matters

The appetite to pick up anything and optimize the hell out of it

Bonus Points

Hands-on experience with Multimodal LLMs, omni models, audio-language models, video-language models, speech generation, or real-time interactive agents

Research or implementation experience with flow matching, diffusion models, rectified flows, autoregressive generation, neural codecs, or related generative modeling methods

Multiple tier 1 publications, or a paper that received significant attention (best paper award, broad adoption, high citation impact for its age)

Olympiad medals or finalist-level results in IMO, IPhO, IOI, IChO, IBO, IMC, or equivalent

Codeforces grandmaster, ICPC world finals, Putnam fellow, Kaggle grandmaster, or similar

Open-source contributions to major ML frameworks or research codebases

A track record of independent projects that made something noticeably faster, smaller, or better

Compensation

$200,000 – $250,000 annualized base salary during the 3-month fellowship (paid as a prorated stipend). Fellows who convert to a full-time Member of Technical Staff role step into a base salary of $250,000 – $350,000 plus meaningful equity.