Member of Technical Staff - Research Fellow

3-month research fellowship for early-career researchers working on frontier Multimodal LLMs, generative modeling, and real-time audiovisual AI. Own a research problem in pretraining, post-training, RL, evaluation, or multimodal modeling. Strong PyTorch and first-author tier-1 paper required.

About the job

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

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

Benefits

Health: HSA plan with ~$2,000 in annual company contributions
Time off: 15 days of PTO plus public holidays, and we close the office for a full week at year-end
Food: Lunch, drinks, and snacks on us every workday
Commuter benefits: We help cover the cost of getting to the office
401(k): In the works

Skills

PyTorch, Deep Learning, Multimodal Llms, Generative Modeling, Flow Matching, Diffusion Models, Audio-Language Models, Video-Language Models, Speech Generation, Real-Time Interactive Agents