Zyphra
Full TimeDesign and test novel model architectures and training methodologies to improve efficiency and address bottlenecks in AI models, working closely with the pre-training team to integrate insights into next-generation systems. You'll need strong research intuition, rapid prototyping ability in PyTorch, and experience taking projects from conception through rigorous experimentation. Background in long-term memory, RAG systems, reinforcement learning, or alternative credit assignment approaches is valued. Based in San Francisco.
Written from this posting by Neural Jobs AI. The full description is below.
As a Research Engineer - Model Architectures, you will be a core contributor to Zyphra’s AI Architecture Research Team. This will involve designing and rigorously testing novel model architectures and training methodologies, with a focus on improving core modeling capabilities (e.g., loss per flop or loss per parameter) and addressing fundamental bottlenecks in contemporary models. You will also work extremely closely with our pre-training team, who will integrate your insights into our next-generation models.
Strong research taste and intuition
The ability to work through a research project from conception to execution to write-up
Strong implementation and prototyping ability can take an idea from conception to experimentation extremely quickly
The ability to work well and cooperate with others in a high-paced research setting
Curiosity, interest, and joy in understanding intelligence.
Previous experience with long-term memory, RAG/retrieval systems, dynamic/adaptive computation, and alternative approaches to credit assignment
Experience with reinforcement learning, control theory, and signal processing
Generally, a joy in inventing and seriously assessing ‘crazy’ ideas, and the ability to have a unique perspective on things
Understanding of modern training pipelines and the hardware requirements to design efficient architectures for GPU hardware
Strong grasp of proper experimental methodology for running rigorous ablations and other hypothesis testing
High proficiency with PyTorch and Python.
Strong ability to jump into large pre-existing codebases and rapidly get up to speed and become productive
Previously published machine learning research in well-respected venues
Postgraduate degree in a scientific subject (Computer Science, EE/EECS, Math, Physics)
Our research methodology is to make grounded, methodical steps toward ambitious goals. Both deep research and engineering excellence are equally valued
We strongly value new and crazy ideas and are very willing to bet big on new ideas
We move as quickly as we can; we aim to minimize the bar to impact as low as possible
We all enjoy what we do and love discussing AI
Comprehensive medical, dental, vision, and FSA plans
Competitive compensation and 401(k) plan
Relocation and immigration support on a case-by-case basis
In-office snacks and meals provided
Unlimited PTO and company holidays
In-person team in San Francisco with a collaborative, high-energy environment
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