AI Scientist - Biomedical Multimodal Modeling

Xaira Therapeutics is hiring an AI Scientist - Biomedical Multimodal Modeling in South San Francisco, United States. It pays $170k-$240k a year and Level rates it ; you can apply on Xaira Therapeutics.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include PyTorch, JAX and Python.
Level lists 30 other open roles at Xaira Therapeutics.

AI in this role

Develop multimodal foundation models and representation learning techniques for biological and molecular discovery.

pytorchjaxpython

deep-learningrepresentation-learninggenerative-modelingmultimodal-learningmachine-learning

About Xaira Therapeutics

Xaira is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The company is leading the development of generative AI models to design protein and antibody therapeutics, enabling the creation of medicines against historically hard-to-drug molecular targets. It is also developing foundation models for biology and disease to enable better target elucidation and patient stratification. Collectively, these technologies aim to continually enable the identification of novel therapies and to improve success in drug development. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London.

About the Role
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.

What You’ll Do

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

What We’re Looking For

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.)

Relevant Experience

Work on multimodal learning or cross-domain representation learning
Experience with image data, molecular / omics-like data, or both
Familiarity with large-scale training

Bonus

Exposure to biological or scientific datasets
Experience with paired or partially aligned multimodal data
Comfortable working in open-ended, evolving problem spaces

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $170,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

How we rate this

AI Scientist - Biomedical Multimodal Modeling at Xaira Therapeutics rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

AI Scientist - Biomedical Multimodal Modeling is an open job at Xaira Therapeutics.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $170k-$240k a year.
The role is based in South San Francisco, California, United States.
The job was posted on May 4, 2026.
Applications are handled by Xaira Therapeutics. Apply on Xaira Therapeutics

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Deep learningRepresentation LearningGenerative ModelingMultimodal LearningMachine learningPyTorchJAXPython

Questions you could be asked

Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where representation learning was part of your work. What did you do?
Tell me about a project where generative modeling was part of your work. What did you do?
Tell me about a project where multimodal learning was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Deep learning, Representation Learning, Generative Modeling, Multimodal Learning, and Machine learning. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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