Senior AI Researcher - Applied Models

About Immunai:

Immunai is an AI-driven platform company focused on improving drug discovery and development by decoding the human immune system.

We combine large-scale single cell immune data, advanced machine learning, and strong engineering to help pharmaceutical and research partners make better, more informed decisions throughout the drug development process.

Our long-term goal is to reduce drug development failure rates and help more effective medicines reach patients. We’re building this platform thoughtfully and collaboratively, bringing together expertise across biology, AI, engineering, and business.

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 work closely with Immunai’s delivery team, translating real-world clinical and scientific questions into rigorous AI and machine learning solutions. In this role, you will lead the development of methodologies, models, and benchmarking frameworks that address complex clinical problems using Immunai’s unique immune-cell data. Your work will directly impact how our partners understand biology, evaluate hypotheses, and make decisions.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

• Partner with the collaborations team and scientists to frame complex clinical and biological questions as well-defined data science and modeling problems.
• Design, implement, and evaluate the right analytical and modeling approaches for each problem, including robust benchmarking and validation strategies.
• Clearly communicate results, limitations, and tradeoffs to internal teams and external partners, enabling confident, data-driven decisions.
• Establish best practices for rigor, reproducibility, evaluation, and documentation across delivery-focused data science work.
• Work hand-in-hand with immunologists, computational biologists, AI scientists, and engineers to ensure solutions are scientifically sound and production-aware.
• Translate modeling solutions into engineered and iterable products used by the internal collaborations team.
  
  

• MSc or PhD in Computer Science, Statistics, Mathematics, Machine Learning/Data Science, Physics, Computational Biology, or a related field
• At least 4 years of industry experience
• Strong foundation in machine learning - neural networks/classical machine learning
• Hands-on experience with Python-based data science and ML tooling
• Proven experience working with large, complex datasets (biological data preferred)
• Experience with MLOps/DataOps practices for robust and reproducible ML training and evaluation pipelines, including experience with benchmarking tools and pipeline optimization
• Experience in statistics, probability, mathematical modeling and experimental design - preferred
• Experience using transformer-based models for applied solutions - preferred
• Experience in biotech, life sciences, or healthcare — preferred
  
  

• 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