Research Engineer -- Vision and Vision-Language Models

Zyphra•San Francisco, CA

2d•Onsite

About The Position

As a Research Engineer - Vision & Vision-Language Models, you will be a core contributor on Zyphra’s Vision Team, building the next generation of models for image understanding, computer use, and other agentic visual tasks. You will work across the full model development stack, from sourcing and generating data to pretraining, post-training, reinforcement learning, and evaluation. The Vision Team owns its models end-to-end, and you will have the opportunity to contribute wherever you can have the greatest impact. We care strongly about rate of learning, research taste, and ability to execute. Previous experience training vision-language models is valuable, but not required.

Requirements

Strong research taste and intuition, with the ability to take ambiguous problems from conception to experimentation and execution
Strong implementation and prototyping ability; you can turn ideas into experiments quickly
A high rate of learning and an ability to rapidly become effective in unfamiliar technical areas
Strong general machine learning intuition and an interest in understanding the full model development stack
The ability to work well with others in a high-paced research setting
Excellent communication and collaboration skills, and the ability to work effectively across both research and engineering implementation at scale

Nice To Haves

Experience working with vision, vision-language, video, or other multimodal models or datasets is highly valuable
Experience training vision-language models is a plus, but not required
Experience with large-scale model pretraining, post-training, reinforcement learning, or related methodologies
Experience sourcing, generating, or curating vision datasets, including synthetic data generation
Familiarity with image processing tools, libraries, or pipelines
Experience with computer use agents, visual agents, GUI understanding, or other multi-turn multimodal tasks is a plus
Experience with frontend development, web frameworks, UI/UX implementation, or mobile development is valuable, particularly for computer use and interface-understanding tasks
Experience training models on large-scale, multi-node GPU clusters
Strong grasp of experimental methodology for running rigorous ablations and hypothesis testing
Understanding of large-scale, highly parallel data processing pipelines
Proficiency with PyTorch and Python
Strong ability to dive into large pre-existing codebases and rapidly get up to speed
Published machine learning research in well-respected venues is a plus
Postgraduate study in a scientific or technical field such as Computer Science, EE/EECS, Mathematics, Physics, or Machine Learning is a plus, but we care more about demonstrated ability and trajectory than credentials

Responsibilities

End-to-end pretraining and post-training of vision-language models
Large-scale vision and multimodal training runs
Vision and multimodal dataset sourcing, generation, curation, processing, and evaluation
Reinforcement learning and other post-training methodologies for vision-language models
Computer use, visual agents, and other multi-turn agentic vision tasks
Architecture, data, and training methodology ablations and improvements
Performance optimization of our training and data processing stacks