Machine Learning Engineer

Title: Machine Learning Engineer
Location: South San Francisco, CA
Position Type: Contract
Rate Range: $37.44 - $83.44

MindSource is looking for a Machine Learning Engineer to join our client's team in South San Francisco, CA. They will be developing and deploying advanced computational methods for molecular design. This is a 12-month hybrid contract.

About the Role

• Build pipelines for probabilistic molecular property prediction and Bayesian acquisition to power active learning-driven drug discovery.

• Engineer workflows for molecular generative modeling and other innovative design approaches.

• Collaborate with machine learning scientists, engineers, computational chemists, and biologists.

• Partner with therapeutic development teams to analyze existing molecules and design new candidates.

• Contribute to ongoing initiatives while driving new research directions.

Qualifications

• PhD in Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics, or related quantitative field OR MS + 3+ years of relevant industry experience.

• Demonstrated expertise in production-ready ML workflows (e.g., PyTorch + Lightning + Weights & Biases).

• Strong track record of achievement (e.g., high-impact first-author publication or equivalent).

• Excellent written, visual, and verbal communication skills.

Preferred Experience

• Knowledge of physical modeling (e.g., molecular dynamics) and cheminformatics (e.g., RDKit).

• Background in molecular property prediction, computational chemistry, de novo drug design, medicinal chemistry, small molecule design, self-supervised learning, geometric deep learning, Bayesian optimization, probabilistic modeling, or statistical methods.

• Hands-on experience with Python, PyTorch, Torch Geometric, PyTorch Lightning, RDKit, and BoTorch.

• Public portfolio of computational projects (e.g., GitHub).