Senior AI Scientist - Multimodal Imaging & Genomics

Vivodyne; San Francisco (CA); On-site; USD 220,000 - 270,000; Full time

Job summary

Vivodyne, Inc. in Brisbane, California, is seeking an AI Senior Scientist to advance large-scale models and Generative AI for immersive biological imaging and multi-omics data.

You'll lead production-grade algorithms and collaborate with biologists, engineers, and AI specialists to turn rich tissue imagery into actionable scientific insights. The role emphasizes model development (Transformers, Diffusion, hybrid architectures), scalable data pipelines, and responsible ML practices.

Qualifications

• PhD or equivalent in a relevant field with strong ML background.
• Proven expertise deploying large ML models (Transformers, Diffusion) in Generative AI.
• Experience with image processing and large-scale model training.

Responsibilities

• Scientific Innovation — align objectives with stakeholders and push new AI ideas.
• Model Development — lead development of cutting-edge ML models for imaging and omics.
• Data Pipeline Optimization — build scalable pipelines on AWS with MLOps practices.
• Multimodal Integration — integrate multi-omics data with imaging to improve phenomics.
• Collaboration & Communication — work with engineers, biologists, and robotics teams.
• Scientific Rigor & Leadership — maintain rigorous research practices and documentation.
• Scalability & Efficiency — design modular, scalable, cost-efficient compute systems.

Skills

Transformers

Diffusion models

Multi-modal models

Generative AI

Image processing

MLOps on AWS

Kubernetes

Education

PhD in Computer Science or related field

Tools

AWS

Kubernetes

Job description

Vivodyne, Inc. in Brisbane, California, is seeking an AI Senior Scientist to advance large-scale models and Generative AI for immersive biological imaging and multi-omics data.

You'll lead production-grade algorithms and collaborate with biologists, engineers, and AI specialists to turn rich tissue imagery into actionable scientific insights. The role emphasizes model development (Transformers, Diffusion, hybrid architectures), scalable data pipelines, and responsible ML practices.