AI Scientist - Biomedical Multimodal Modeling

Xaira Therapeutics • South San Francisco, CA

6d

About The Position

We are building foundation models for biological systems, focusing on learning from complex, multimodal data. Our approach combines representation learning and generative modeling to capture structure, variation, and latent organization in high-dimensional settings. We work with both image-based data and high-dimensional molecular (omics) measurements, treating them as complementary views of the same underlying system. Our goal is to develop models that can both encode rich representations and generate or infer missing aspects from partial observations.

Requirements

• Strong background in deep learning, especially in modern architecture
• Experience with representation learning (self-supervised, contrastive, masked modeling, etc.)
• Experience with generative modeling (diffusion, autoregressive models, VAEs, or related approaches)
• Proficiency in Python, ML frameworks, and CI/CD (PyTorch, JAX, etc.)

Nice To Haves

• Work on multimodal learning or cross-domain representation learning
• Experience with image data, molecular / omics-like data, or both
• Familiarity with large-scale training
• Exposure to biological or scientific datasets
• Experience with paired or partially aligned multimodal data
• Comfortable working in open-ended, evolving problem spaces

Responsibilities

• Develop multimodal foundation models spanning image and molecular data
• Design approaches that unify representation learning and generative modeling
• Train large-scale models on structured, high-dimensional datasets
• Explore cross-modal alignment, prediction, and generation
• Build scalable systems for data processing, training, and evaluation
• Work in a research-driven environment with evolving problem definitions

Benefits

• competitive compensation and benefits package
• open, flexible, and friendly work environment
• platform to develop their long-term careers
• base salary
• bonus
• equity

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed