Overview
Skills
Job Details
AI Research Scientist/Engineer
Menlo Park, CA | On-Site | Full-Time/Direct Hire
Client Opportunity | Through Phizenix (WBENC & Minority-Certified Recruiting Partner)
Join a trailblazing AI startup 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
PhD in Computer Science, Machine Learning, or a related field
Hands-on experience with PyTorch and LLM fundamentals (transformers, KV caching, etc.)
Familiarity with diffusion models and distributed model training
Solid research-to-production mindset with 2+ years in an ML/AI role
Bonus Points For
Training LLMs from scratch and optimizing large-scale runs
Advanced training tactics (e.g., mixed precision, gradient accumulation)
Experience with cross-modal modeling and inference frameworks like vLLM, TensorRT
A background in model efficiency, optimization theory, or infrastructure-aware research
At Phizenix, we’re proud to partner with diverse and inclusive teams building AI that matters. If you're ready to build, innovate, and publish with one of the boldest teams in AI—this is your moment.