Senior Researcher - Diffusion-Based Large Language Models

Propose and develop novel research ideas to advance the state of the art in diffusion-based language models and generative modeling for text (and possibly multimodal).

Design and study non-autoregressive and diffusion-style architectures for LLMs, including discrete/continuous diffusion, denoising objectives, and hybrid transformer–diffusion models.

Participate in applied research projects focused on: scaling diffusion LLMs to long context, improving sample quality and controllability, and reducing inference latency and compute costs.

Deliver end-to-end projects: design and run experiments, implement and debug large-scale training pipelines, analyze results, and clearly communicate findings to both technical and non-technical stakeholders.

Collaborate with data and infra teams on data curation, evaluation, and post-training for diffusion LLMs (e.g., fine-tuning, RLHF/feedback, safety, and robustness).

Publish research in top-tier machine learning and NLP venues and contribute to open-source libraries, benchmarks, or model releases where appropriate.

(If Senior) Supervise and mentor a small group of researchers and engineers to deliver projects and publish conference papers.

Track advances across diffusion models, LLMs, and the broader AI ecosystem, and translate new developments into actionable research directions for the team.