Head of AI

Subsense • Palo Alto, CA

2d

About The Position

We’re looking for a Head of AI to build and lead our AI-driven discovery platform — from virtual material generation to closed-loop validation with experimental data.
You will define how AI becomes a core engine of Subsense: generating novel nanoparticle designs, guiding synthesis, accelerating IP creation, and enabling a scalable, automated discovery pipeline.
This is a rare opportunity to own AI at the core of a new scientific paradigm.
We’re looking for someone who doesn’t wait for direction, but proactively explores the frontier where biotech meets AI. Someone who gets their hands dirty experimenting with what’s possible.
You believe generative AI can dramatically accelerate and transform the way biotech labs operate—and you’re excited to push that belief into reality with the right team and resources, by building and testing things that have never been done before.

Requirements

• 8+ years in AI / ML, with strong focus on applied scientific or deep-tech problems
• Experience building and deploying ML models in: materials science, chemistry, biology, or physics (preferred) or other complex, data-sparse domains
• Proven track record of: turning models into real-world outcomes
• working with experimental or noisy datasets
• Strong experience with: generative models / optimization systems
• simulation-informed ML or hybrid modeling approaches
• data pipelines and iterative learning systems
• Ability to work closely with experimental scientific teams
• Experience leading or mentoring technical teams

Nice To Haves

• Background in: materials discovery / computational chemistry
• nanoparticle research
• bio/chem ML or physics-informed ML
• Experience building AI platforms (not just models)
• Startup or zero-to-one environment experience
• IP generation/patent exposure

Responsibilities

• Build and lead the AI platform from scratchfor: virtual generation of novel biocompatible magnetic nanoparticles
• synthesis guidance and optimization
• prediction of biological and physical properties
• Integrate experimental data into model fine-tuning loops (CRO + in-house)
• Partner with leading AI companies to accelerate and enhance our biotech development
• Drive creation of new IP through AI-generated materials, compositions, and model frameworks
• Partner closely with R&D to translate AI outputs into real-world synthesis and validation
• Establish a scalable pipeline: generate → prioritize → synthesize → test → learn → iterate
• Lead transition from outsourced validation (CROs) to partially in-house AI-guided experimentation
• Define and implement data infrastructure, datasets, and feedback loops
• Build toward full-stack automation of discovery (early stage)
• Hire and lead a high-performance AI / ML team over time

What This Job Offers

• Job Type: Full-time
• Career Level: Executive
• Education Level: No Education Listed