Machine Learning Engineer (Molecular Design)

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.