*Please note, the role is remote and candidates should be based in Poland.
Machine learning lies at the core of insitro’s approach to rethinking drug development. Our team is responsible for the small molecule machine learning platform at insitro, and our responsibilities include design of high-throughput data generating experiments, design and execution of ML driven solutions for accelerating key problems in the drug discovery space, and creation of APIs and tooling for making the entire process reproducible and faster over time.
You will be joining insitro’s first satellite hub that is emerging in Poland. Initially, this role will be based “remote”, and you may work from your home office. As a ML Engineer (Chemistry), you will work closely with a cross-functional team of computational chemists, cheminformaticians, data scientists, and ML engineers to identify key areas where ML could make an impact, design fit-for-purpose small molecule datasets that can answer those questions, and build ML models on top of such datasets.
Your job will be to deeply dive into creating and understanding molecular and DNA encoded library datasets, defining rigorous data splits, developing novel molecular featurization and modeling recipes, and integrating information from differing sources to deliver production quality ML models that can rapidly accelerate therapeutic programs. You will work as part of a team to solve problems in improving protein-drug binding affinity whilst avoiding toxicity issues and minimizing off-target interactions. Along the way, you will learn a broad range of scientific, mathematical, and engineering skills, receive close mentoring from senior scientists and engineers, guide and mentor junior scientists and engineers, build lasting relationships with your colleagues, and help shape insitro’s culture, strategic direction, and outcomes. Join us, and help make a difference to patients!
Nice to Have
Benefits at insitro
insitro is a drug discovery and development company using machine learning and data generation at scale to transform the way that drugs are discovered and delivered to patients. We rely on human genetic cohorts, human-derived cellular disease models, and high-throughput biology and chemistry to identify coherent patient segments, actionable therapeutic targets, and new or existing chemical matter. The goal is to deliver predictive insights to improve the probability of success and reduce the number of costly dead ends along the R&D journey. The company has established collaborations with Gilead in NASH and Bristol Myers Squibb in ALS and is building a pipeline of wholly owned and partnered medicines leveraging its unique insights on patient biomarkers, targets, and molecules. insitro is located in South San Francisco, CA and has raised over $600M from top tech, biotech, and crossover investors since formation in 2018. For more information on insitro, please visit the company’s website at www.insitro.com.
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