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 seeking a highly motivated and experienced LLM/ML Agentic AI Researcher to lead the technical development of our agentic AI interpretation framework. This hands-on role involves designing, building, and evaluating AI agents that interpret complex biological data.
You will be at the forefront of developing a sophisticated scientific reasoning system that leverages Large Language Models (LLMs) to provide structured, biologically-grounded explanations. Collaborating closely with immunologists, machine learning researchers, and technical leadership, you'll shape how we derive insights at a systems level, pushing the boundaries of AI in biology.
Location: Ramat Gan, Israel (Hybrid role)
What will you do?
- Design, prototype, and build LLM-based agentic systems that reason over biological data, scientific literature, model outputs, and internal tools.
- Develop agents capable of structured reasoning, hypothesis generation, explanation, planning, tool use, and iterative scientific analysis.
- Build robust evaluation frameworks for agentic systems, including automated and human-in-the-loop evaluation pipelines.
- Define and implement benchmarks, metrics, and test suites for measuring agent performance, including reasoning quality, biological grounding, factuality, robustness, reproducibility, and usefulness.
- Work closely with AI researchers, computational biologists, immunologists, and product teams to translate scientific needs into measurable AI capabilities.
- Create evaluation datasets and benchmark tasks that reflect real-world biological and therapeutic reasoning problems.
- Analyze agent behavior, failure modes, hallucinations, tool-use errors, reasoning gaps, and grounding issues.
- Contribute to the architecture of production-grade AI systems, including agent orchestration, retrieval, tool calling, memory, planning, and monitoring.
- Stay up to date with the latest developments in LLMs, agentic AI, evaluation methodologies, and scientific AI systems.
- Help turn research prototypes into reliable products used by internal teams and external partners.
Required qualifications:
- MSc or PhD in Computer Science, Electrical Engineering, Computational Biology, Statistics, Mathematics, or a related quantitative field.
- Strong background in machine learning, data science, statistics, or computational modeling.
- Hands-on experience building with LLMs and agentic AI systems.
- Proven ability to design evaluation methodologies for AI systems, especially LLM-based or agent-based systems.
- Experience working with LLM APIs such as OpenAI, Anthropic, Google, or open-source LLMs.
- Experience with agent frameworks or orchestration tools such as LangGraph, LangChain, or similar systems.
- Experience defining benchmarks, metrics, validation sets, scoring methods, or automated evaluation pipelines.
- Strong Python skills and ability to write clean, production-aware research code.
- Ability to work with complex, noisy, high-dimensional data.
- Strong communication skills and ability to collaborate with experts from different disciplines.
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 have a growth mindset
- You are candid, authentic, and transparent
When you apply for a role at Immunai, we process your personal data (such as CV, contact details, and professional background) to assess your suitability for current and future roles. Your information may be shared internally with relevant employees and stored or processed by trusted service providers, some of whom may be located outside your country of residence. You can read more about how we process data here: https://www.immunai.com/privacy-policy/.
Skills Required
- MSc or PhD in Computer Science, Electrical Engineering, Computational Biology, Statistics, Mathematics, or related quantitative field.
- Strong background in machine learning, data science, statistics, or computational modeling.
- Hands-on experience building with LLMs and agentic AI systems.
- Proven ability to design evaluation methodologies for LLM-based or agent-based AI systems.
- Experience working with LLM APIs such as OpenAI, Anthropic, Google, or open-source LLMs.
- Experience with agent frameworks or orchestration tools such as LangGraph, LangChain, or similar systems.
- Experience defining benchmarks, metrics, validation sets, scoring methods, or automated evaluation pipelines.
- Strong Python skills and ability to write clean, production-aware research code.
- Ability to work with complex, noisy, high-dimensional data.
- Strong communication skills and ability to collaborate with experts from different disciplines.
What We Do
Immunai is a biotech company using single-cell genomics, machine learning, and software engineering to map and reprogram the immune system. Its AMICA data foundation and AI models support discovery and development of therapeutics, including applications in cancer, autoimmune disease, and immuno-oncology. The company partners with biopharmaceutical companies and research institutions to identify targets, biomarkers, mechanisms of action, and other clinically relevant insights.
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