Job description

Drug discovery is a hierarchical reinforcement-learning problem with a vast action space and years-long horizon. Scientists design and synthesize molecules that they predict will be potent, safe, and readily absorbed into the body, but this typically requires years of iteration in the lab and millions of dollars to develop a molecule that is ready for testing in human. At Inductive, we're building the AI and machine learning tools to radically accelerate this process. Our state-of-the-art predictive models and medicinal chemistry agents identify the right compounds to make at the right time, while our AI-integrated lab shortens the time to synthesize and test them. 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. 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 generate and prioritize molecules for synthesis - Build agents that can analyze 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 Who you are: - You have 4+ years of experience as a Machine Learning Scientist, Machine Learning Engineer, 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, JAX, TensorFlow) - 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 Working at Inductive 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.

Requirements

Must-haves

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.
Develop machine learning models to predict molecular properties from chemical structures
Develop novel algorithms for generate and prioritize molecules for synthesis
Build agents that can analyze 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, 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, JAX, TensorFlow)
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

Nice-to-haves

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
Working at Inductive

Application prep

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Keywords to mirror

aimachine learningmlpython

Platform: ashby
Effort: quick

Benefits

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Dental

Vision

Pto