Machine Learning Scientist

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.

About the role:

As a Machine Learning Scientist at Immunai, you will join our Machine Learning team researching, building, and deploying our core scRNA representation models. These models are used to synthesize large amounts of single-cell immunological data, bridging therapies, indications, data modalities, and biological systems (in vitro, in vivo, in sapiens) and connecting them to drug trial results in a meaningful manner. Your purpose will be to impact decisions during drug development based on the prediction of the team's models.

The challenges of varied big data made of cell specific measurements of millions of cells present challenging problems for deep interpretable representation modeling focused on but not limited to the latest transformer modeling architectures.

You will collaborate very closely with an experienced ML team as well as computational biologists and immunologists to ensure the resulting product is successful and used throughout Immunai’s internal and external projects.

Location - Tel Aviv, Israel

What will you do?

• Research, develop, and deploy state-of-the-art and classic machine learning models based on single-cell data from immunological datasets
• Develop and own scalable production pipelines driven by the core models
• Stay updated on latest advancements in single-cell omics and machine learning research
• Collaborate with stakeholders across software engineering, computational biology, and immunology to successfully apply ML models for impacting clinical trials
• Mentor and provide technical guidance to team members

Required qualifications:

• MSc or Ph.D. in computer science, bioengineering, computational biology, or related discipline
• MSc + 5 years of relevant industry experience or PhD with 1-4 years of relevant industry experience, specifically hands-on deep learning experience
• Demonstrated experience leading projects using custom deep learning models to solve biological problems
• Demonstrated experience working with large amounts of biological data, preferably with single-cell omics data
• Strong technical abilities in Python and ML libraries (sklearn, PyTorch, an advantage: DeepSpeed/Zero or similar)
• Evidence of engagement with open source projects and community
• Excellent written and verbal communication skills.

Desired personal traits:

• 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 constantly challenge your own assumptions, pushing for continuous improvement
• You have a growth mindset
• You make decisions that favor the company, not yourself or your team
• You are candid, authentic, and transparent