(Senior) ML Engineer/Scientist, Small Molecules

The Opportunity
Machine learning lies at the core of insitro’s approach to rethinking drug development. As part of the small molecule machine learning group, you will lead the development of cutting edge machine learning methods that solve key problems in the drug development process. You will work in cross-functional teams whose members span drug-discovery, high-throughput biology and chemistry, machine learning, and data engineering. 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!  
 

About You
-BS, MS, or Ph.D. in a quantitative subject area such as computer science, chemistry, statistics, mathematics, physics, engineering, or equivalent practical experience
- Working knowledge of computational chemistry, including classic QSAR modeling, ligand and structure based drug-discovery, docking, virtual screening, library design etc 
- Expertise in one or more general-purpose programming languages (such as Python, C/C++, or Scala) 
- Demonstrated ability to write high-quality, production-ready code (readable, well-tested, with well-designed APIs)
- Experience with at least one high-end ML development environment (Tensorflow, Pytorch, Caffe, etc)
- Experience with at least one of the cheminformatics toolkits (OpenEye/RDKit/Schrodinger suite, etc)
- Demonstrated ability to develop novel machine learning methods that go beyond putting together of existing code, and to apply problem-solving skills to complex issues
- Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
- Desire to continuously self-improve and a passion for making a difference in the world


Nice to Have 
- Experience with small molecules and/or DNA encoded library datasets
- Working knowledge of statistics and various flavors of statistical modeling techniques
- Experience with building and debugging graph convolutional neural networks and generative models
- Experience with scalable machine learning, including the application to large datasets (100TB+)
- Proficiency in Linux environment (including shell scripting), experience with database languages (e.g., SQL, No-SQL) and experience with version control practices and tools (Git, Perforce, etc.)
- Familiarity with cloud computing services (AWS or GCP


Benefits at insitro
- Excellent medical, dental, and vision coverage; insitro pays 100% of premiums for employees
- Excellent mental health and well-being support
- Open vacation policy
- Access to free onsite baristas and cafe with daily lunch and breakfast
- Access to free onsite fitness center
- Commuter benefits
- Paid parental leave
- Competitive pay and 401(k) matching

About 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 enabling 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.