Machine Learning Engineer

Job Title: Machine Learning Engineer (Molecular Design)

Location: Hybrid - Bay Area, CA

Job Description:
We are seeking a Machine Learning Engineer with expertise in molecular design to support cutting-edge drug discovery initiatives. The role focuses on developing and optimizing ML workflows for molecular property prediction and generative modeling to accelerate research and innovation.


Key Responsibilities:

• Develop and implement machine learning models for molecular property prediction and generative molecular design.
• Collaborate with cross-functional teams to integrate ML workflows into drug discovery pipelines.
• Analyze and interpret complex molecular datasets to guide experimental design.
• Stay up-to-date with the latest research and publications in molecular modeling and computational chemistry.

Qualifications:

• 3-5 years of experience in machine learning, computational chemistry, or molecular modeling, or a PhD with relevant publications in molecular design.
• Strong programming skills in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
• Hands-on experience with generative models, predictive modeling, and molecular simulations.
• Excellent analytical, problem-solving, and communication skills.

Preferred:

• Experience in drug discovery or pharmaceutical research environments.
• Familiarity with cheminformatics tools and molecular libraries.