ML Researcher: Build Human-Toxicity AI for Drug Discovery

Axiom; San Francisco (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Axiom is building the first accurate AI systems to replace animal testing with human-relevant predictive models. You will work on end-to-end ML and agent systems across wet-lab data, multimodal inputs, and mechanistic reasoning to predict human toxicity.

Join a founding team focused on liver injury prediction, collaboration with pharma, and deployment of scalable ML solutions that inform drug discovery decisions.

Qualifications

• Exceptional ML talent with a track record of impactful work.
• Deeply technical, comfortable debugging and scaling training runs.
• Experience handling noisy, multimodal biological data and real-world datasets.
• Ability to translate research ideas into deployable systems and products.

Responsibilities

• Define end-to-end ML and agent systems for wet-lab data generation and analysis.
• Build models relating chemistry, biology, dose, exposure, and toxicity in humans.
• Train multimodal models on chemical structures, imaging, omics, and clinical data.
• Develop foundation models for biological images, molecules, and multimodal outputs.
• Architect models predicting human toxicity across dose, Cmax, and structure.
• Aggregate and interpret embeddings across assays, doses, times, modalities, compounds.
• Collaborate with biologists, chemists, and data engineers to improve model performance.
• Own the research-to-product loop: prototype, train, evaluate, ship, observe, improve.

Skills

PyTorch

JAX

TensorFlow

Python

Multimodal ML

Biology data

Tools

GPU clusters

Cloud computing

Job description

Axiom is building the first accurate AI systems to replace animal testing with human-relevant predictive models. You will work on end-to-end ML and agent systems across wet-lab data, multimodal inputs, and mechanistic reasoning to predict human toxicity.

Join a founding team focused on liver injury prediction, collaboration with pharma, and deployment of scalable ML solutions that inform drug discovery decisions.