Nuance Research Fellow

Nuance Labs•Seattle, WA

7d•$200,000 - $250,000•Onsite

About The Position

The Nuance Research Fellowship is a 3-month engagement for early-career researchers who want to do serious work at the frontier of multimodal AI — and to find out, alongside us, whether Nuance is where they want to spend the next chapter of their career. You’ll contribute directly to one or more of our research workstreams: pretraining, post-training, RL, evaluation, data, multimodal modeling, or inference, working alongside people who’ve built these systems before. At the end of three months we’ll decide together whether to convert to a full-time Member of Technical Staff role, with enough lead time for you to plan your next step either way. Fellows who convert step into MTS-level scope and ownership from day one. We build photorealistic digital humans with full-duplex, real-time audiovisual interaction. There are open problems across the entire ML stack — training omni models from scratch, aligning them, evaluating real-time conversational behavior, shipping at sub-500ms latency. Plenty are still unsolved, and we want people who find that exciting.

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
Genuine interest in joining Nuance full-time after the fellowship. This isn’t an internship or a side project — we are looking for long-term partners on this journey
BS, MS, or PhD in CS, ML, math, physics, EE, or a related field — completed or in the final stretch
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

Nice To Haves

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
Hands-on experience with multimodal models (audio, video, language) or real-time systems
Open-source contributions to major ML frameworks or research codebases
A track record of independent projects that made something noticeably faster, smaller, or better

Responsibilities

Contribute directly to a research workstream from week one — pretraining, post-training, RL, evaluation, data, multimodal modeling, or inference
Read papers, reproduce key results, and bring promising ideas into our stack
Run experiments rigorously: design, instrument, debug, and draw conclusions from training and eval runs
Build evaluation harnesses, benchmarks, and analysis tooling the team relies on
Take research-grade prototypes and turn them into something that ships
Work closely with senior researchers and engineers across the team; ramp on the stack fast
At the end of three months, decide together whether full-time MTS is the right next step