AI Research Scientist
AI Research Scientist
Menlo Park, CA | On-Site
Full-Time/Direct Hire
Seeking top-tier PhDs (Bay Area preferred) with ICML/ICLR publications in LLM training and inference optimization—no vision/audio, just pure language; diffusion model experience a plus.
Join a trailblazing Dillusion-LLM startup Company that's reinventing how large language models are built—with diffusion-powered LLMs that generate faster, adapt smarter, and handle multimodal data like no other.
We’re looking for a Research Scientist / Engineer who’s ready to move beyond traditional autoregressive methods and help shape the next wave of generative AI. You'll collaborate with pioneers in AI research, design novel model architectures, and scale your ideas from paper to production.
What You'll Be Doing
- Design and refine LLM architectures built on a diffusion-first paradigm
- Develop cutting-edge training strategies and custom loss functions
- Translate research into real-world systems for enterprise-scale deployments
- Explore constraint-aware generation and controlled outputs
- Push the limits of model efficiency, scalability, and multi-modal capabilities
Must-Haves
- Should have a PhD in Computer Science, Machine Learning, or a related field
- Hands-on experience with PyTorch and LLM fundamentals (transformers, KV caching, etc.)
- Brings deep expertise in inference optimization for LLMs, including model quantization, CUDA/GPU tuning, and deployment of VLLMs for low-latency, high-throughput serving.
- Should have recent/or any ICLR/ICML publications in LLM inference optimization would be ideal.
- Familiarity with diffusion models and distributed model training
- Solid research-to-production mindset with 2+ years in an ML/AI role