Senior ML Scientist - Drug Discovery & Quantum AI

Ten63 Therapeutics; Durham (NC); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Equity and annual bonus

Health insurance

401K matching

Cutting-edge compute resources

Fitness center access

Job summary

Ten63 Therapeutics seeks a Senior ML Scientist to advance AI-driven drug design on the BEYOND platform. You will design and train deep learning models, integrate physics-based simulations, and steer model development across computational chemistry workflows.

You will lead multi-GPU training efforts, mentor scientists, and help translate scientific requirements into production-ready AI solutions in a fast-paced, collaborative environment.

Qualifications

• PhD in Computational Chemistry, Chemical Engineering, Chemistry, Computer Science with chemistry focus, or related field, or equivalent industry experience.
• 4+ years of professional experience developing and deploying machine learning models in production environments.
• Expert-level Python programming for scientific software development.
• Experience with multiple neural architectures (CNNs, RNNs, Transformers, Diffusion, GANs) and large-scale GPU training.

Responsibilities

• Design, train and evaluate deep learning models for drug-design applications.
• Lead multi-GPU model training on clusters spanning weeks to months.
• Integrate physics-based simulations with learned models for structure-based drug design.
• Create datasets, splits, and benchmarks reflecting real prospective use.
• Collaborate with chemists and engineers to translate requirements into robust AI solutions.

Skills

Deep learning

Python

GPU training

Molecular simulations

Cheminformatics

PyTorch

TensorFlow

JAX

Education

PhD in Computational Chemistry/related field

Tools

RDKit

OpenMM

Gromacs

Gaussian

Job description

Ten63 Therapeutics seeks a Senior ML Scientist to advance AI-driven drug design on the BEYOND platform. You will design and train deep learning models, integrate physics-based simulations, and steer model development across computational chemistry workflows.

You will lead multi-GPU training efforts, mentor scientists, and help translate scientific requirements into production-ready AI solutions in a fast-paced, collaborative environment.