Senior AI Researcher – Foundation Models

About Immunai:

Immunai is an engineering-first platform company aiming to improve therapeutic decision-making throughout the drug discovery and development process. We are mapping the immune system at unprecedented scale and granularity and applying machine learning to this massive clinico-immune database, in order to generate novel insights into disease pathology for our partners - pharma companies and research institutes. We provide a comprehensive, end-to-end solution - from data generation and curation to therapeutics development, that continuously supports and validates the capabilities of our platform.

As drug development is becoming increasingly inefficient, our ultimate goal is to help bring breakthrough medicines to patients as quickly and successfully as possible.

Immunai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

About the role:

We are looking for a Senior AI Researcher to join Immunai’s foundation models team and help advance large-scale models for single-cell RNA (scRNA) data.

In this role, you will focus on training and improving transformer-based and deep learning models, developing algorithmic solutions to challenging modeling problems, and adapting modern foundation model techniques to biological data. This is a hands-on research position for someone who enjoys building and training deep models, understanding their behavior, and pushing them to perform better.

You do not need prior biology experience — but you should be excited to apply your deep learning expertise to a new scientific domain.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

• Develop, train, and refine transformer-based and related architectures for large-scale scRNA data.
• Tackle challenging modeling problems with thoughtful, principled approaches.
• Apply ideas from NLP and vision (pretraining, self-supervision, transfer learning) to biological data.
• Plan careful experiments, perform ablations, and deeply analyze results to guide model improvements.
• Engage directly with large, noisy biological datasets and build intuition for model behavior in this setting.
• Partner with engineers, data scientists, and biology experts to turn research ideas into working systems.
  
  

• MSc or PhD in Computer Science, Mathematics, Physics, or a related scientific field
• 3+ years of hands-on experience training deep learning models (e.g., transformers, vision models, or related architectures)
• Strong practical experience with PyTorch (or similar frameworks)
• Solid understanding of optimization and representation learning
• Proven ability to develop algorithmic solutions to complex problems
• Strong experience in experimental design, statistical evaluation, and working with large, complex datasets
• Ability and willingness to adapt to a new domain (biology)
  
  

• Experience with large-scale pretraining
• Experience with foundation models
• Experience adapting methods across domains
• Research publications or meaningful research contributions
• Experience in computational biology or biomedical data (a plus, not required)
  
  

• You want to make an impact on humankind
• You prioritize “We” over “I”
• You enjoy getting things done and striving for excellence
• You collaborate effectively with people of diverse backgrounds and cultures
• You have a growth mindset
• You are candid, authentic, and transparent