Join Xaira Therapeutics as an AI Scientist to develop multimodal foundation models for drug discovery using advanced AI techniques.
Posted by employer 5 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 10 hours ago
Not disclosed in this posting: years of experience, visa sponsorship.
Joblaze summary
In this role, the AI Scientist will focus on developing multimodal foundation models that integrate image and molecular data to enhance drug discovery efforts. Key skills include deep learning, representation learning, and generative modeling, with proficiency in Python and machine learning frameworks like PyTorch or JAX being essential. This position is ideal for candidates with a strong background in multimodal learning and experience with complex datasets, particularly in a research-driven environment. Xaira Therapeutics, an innovative biotech startup, emphasizes a collaborative approach to tackling evolving challenges in drug development.
Quick facts
- Is the AI Scientist - Biomedical Multimodal Modeling role remote?
- It's hybrid — Xaira Therapeutics expects some on-site time in South San Francisco, California, United States.
- What's the salary range?
- Xaira Therapeutics lists $170,000–$240,000 for this role.
- Where is the role based?
- Xaira Therapeutics is hiring for this position in South San Francisco, California, United States.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Deep Learning, JAX, PyTorch, Python, generative modeling, multimodal learning.
- What seniority level is this role?
- Xaira Therapeutics targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this AI Scientist - Biomedical Multimodal Modeling role at Xaira Therapeutics.
From the original posting
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.
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