MTS, Machine Learning

We are seeking a Member of Technical Staff, Machine Learning to join our talented, ambitious, and kind team. You’ll innovate on ML methods, work closely with leading drug discovery scientists, and see your work applied directly to real drug programs. You’ll have significant ownership, impact, and opportunity to grow with the company.

What you’ll do:

• Develop machine learning models to predict molecular properties from chemical structures
• Develop novel algorithms for generating ideas for new molecules
• Build agents that can synthesize complex information from drug programs and apply that information strategically toward molecular optimization
• Get your hands dirty by diving deep into our unique, proprietary dataset to iterate on modeling ideas and improve model performance
• Collaborate closely with chemists and software engineers to integrate models into our software platform, which is used by drug discovery scientists across the industry
• Build and optimize scalable infrastructure for model training, deployment, and monitoring
• Engage directly with our scientific users, incorporating their feedback into the product
• Contribute meaningfully to product strategy and company direction

• You have 4+ years of experience as a Machine Learning Scientist, Machine Learning Engineer, Data Scientist, or similar role
• You have a strong scientific background, ideally with a PhD in chemistry, biology, physics, or a related field
• You have expertise in machine learning fundamentals, deep learning architectures, and evaluation approaches
• You are proficient in standard Python-based ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)
• You are comfortable writing high-quality, reusable code and productionizing models for serving in the cloud
• You are excited to dive deep into the science and practice of drug discovery
• You have exceptional written and oral communication skills
• Preferred experience:
• You have graduate-level knowledge of cell / molecular biology or biochemistry, and experience collaborating with wet lab scientists
• Experience with omics modeling (transcriptomics, proteomics, metabolomics, etc)
• Experience with high-content screening and signal processing from microscopy data

At Inductive Bio, we know that the people on the team are what make us great. We offer competitive salary and equity-based compensation; comprehensive healthcare benefits (including dental and vision); and the opportunity to grow along with a rapidly scaling company. We are a passionate, kind, and mature team. Working at a fast growing startup is not always a 9-5 job, but we believe that our employees should have full lives beyond their career.

Compensation Range: $180K - $250K

Drug discovery is a prediction problem. Scientists design molecules that they predict will be potent, safe, and readily absorbed into the body, but ultimately lab experiments must be run to know whether these predictions are accurate. Each one of these experiments can take weeks or months to run, and as a result it costs millions of dollars and takes years to design a molecule that is ready for testing in humans.

At Inductive Bio, we’re using AI to build in silico models that more accurately predict how molecules will behave in experiments, helping scientists make better decisions faster. Our ADMET/PK models have placed first in the world’s largest AI drug discovery competition for ADMET benchmarks three consecutive times, and our technology is already being applied across dozens of biopharma partnerships.

Backed by leading technology and biotechnology investors including a16z, Lux, S32, and Obvious, our team brings together world-class expertise in machine learning and drug discovery.