Machine Learning Engineer
Location: South San Francisco, CA
Rate- $75/hr. On W2
12 Months Hybrid Contract
Client 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.

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).
  Job Type: Contract
  Pay: $70.00 - $78.00 per hour
  Expected hours: 40 per week
  Work Location: In perso

• 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.