AI Engineer (Agent Systems & LLMs)

Palo AltoFull Timemid

Data ScienceMachine Learning EngineerAI EngineerDataData & AI

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Overview

GenBio AI develops multiscale foundation models to decode and simulate human biology.

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Data ScienceMachine Learning EngineerAI EngineerDataData & AI

GenBio AI develops multiscale foundation models to decode and simulate human biology. Our team is accelerating towards an ambitious future where scientists can unlock humanity's biggest challenges in drug discovery, healthcare, and fundamental research with AIDO (AI-Driven Digital Organism): a unified framework for predicting, simulating, and programming biology across all scales. The foundation of this vision begins today as we engineer the virtual cell to model and simulate the fundamental unit of life.

This vision has brought together a talent-dense group of product-minded researchers and engineers dedicated to bringing it to reality. Our team prides itself on our strong engineering culture and highly interdisciplinary and collaborative approach. We are based in Palo Alto, with satellite offices in Paris and Abu Dhabi.

Your job will be to build AI scientists that conduct autonomous biomedical research with GenBio’s virtual instruments and simulators. Because these agents will be executing complex scientific workflows, your primary focus will be designing the biological tasks, environments, and rigorous evaluations required to ensure they produce valid, high-fidelity science. If successful, your contributions will enable rapidly designing and orchestrating end-to-end biological simulation studies for drug design, healthcare, and biotechnology development.

Domain-Specific Agent Evaluation: Design, build, and scale rigorous evaluation frameworks to measure agent reasoning, scientific accuracy, and tool-use performance against real-world biological benchmarks.

Applied Biological Agents: Build and deploy applied AI agents and reasoning world models tailored for complex scientific workflows, orchestrating tasks across drug discovery, computational chemistry, and biological simulation.

Scientific Environment Architecture: Architect fast, secure, and observable environments where AI agents can execute biological simulations.

Research Engineering: Translate experimental research concepts into robust, shippable product features, maintaining high engineering standards while understanding domain-specific use-cases and data types.

Cross-Disciplinary Optimization: Bridge the gap between biological simulation and modern AI infrastructure, optimizing workflows to ensure models are scalable and reliable in production.

Life Science Domain Expertise: Deep, practical knowledge in a specific vertical of biology, chemistry, physics, bioinformatics, or drug discovery. You must understand the science that your agents and AIDO are enabling.

Biological Modeling Portfolio: You must have at least one significant project, ideally an open-source project or notable publication, focused on biological modeling, simulation, or AI applied to the physical or life sciences.

Agentic Systems & Evals: Experience building custom evals for long-horizon optimization tasks and test-time applications. Bonus points if combined with LLM reasoning and agentic applications.

Strong Engineering Foundation: M.S. or Ph.D. in Computational Biology, Computational Chemistry, Biomedical Informatics, Computer Science, or a related discipline, alongside proficiency in software engineering.

0-to-1 Mindset: Experience bootstrapping products in fast-paced startup environments; you are comfortable building from scratch with high autonomy.

Interdisciplinary Communication: Excellence in translating complex biological challenges into engineering requirements, and vice versa, to a highly diverse team of scientists and engineers.