(Senior) Computer Vision ML Engineer - Medical imaging

The Opportunity
Key to insitro’s approach to rethinking drug development is leveraging disease models, genetics, and clinical datasets to link in vitro and cellular phenotypes with patient outcomes.

As a machine learning engineer with expertise in clinical data analysis, you will develop cutting edge deep learning and computer vision tools to analyze and integrate large-scale multi-modal phenotypic datasets, including medical imaging modalities, physiological monitoring, and longitudinal data. You will work with clinical data from randomized clinical trials, large human cohorts with medical imaging datasets, and other sources. You will also work closely with a cross-functional team of life scientists, statistical geneticists, bioengineers and machine learning scientists to integrate human level data with our high-throughput in-house in vitro genomic and phenotypic data to identify therapeutic targets and develop drugs that have high efficacy and low toxicity.

You will be joining an agile and fast growing biotech startup that has long-term stability due to significant funding, but yet is very much in formation. You will have ample opportunities for significant impact. You will work closely with a very talented team, learn a broad range of skills, and help shape insitro’s culture, strategic direction, and outcomes. Join us, and help make a difference to patients!


About You
- Ph.D. in machine learning, computer science, computational biology or a related discipline, or equivalent practical experience (e.g., a Masters degree plus 2 years in relevant industry experience);
- Extensive experience using modern deep learning frameworks (e.g., PyTorch, TensorFlow, Keras) and shallow machine learning model libraries (e.g., scikit-learn, XGBoost); proficiency in Python;
- Demonstrated experience developing computer vision tools for diverse computer vision tasks (e.g. segmentation, recognition, classification, domain adaptation) and ability to rigorously deal with clinical confounders and technical artifacts;
- Proficiency in Linux environment (including shell/Bash scripting), experience with version control practices and tools (e.g., Git) and familiarity with cloud computing services (e.g., AWS or GCP);
- Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions;
- Passion for making a difference in the world.


Nice to Have
- Experience working with biomedical or biophysical imaging modalities;
- Familiarity with workflow management tools or batch scheduling systems (e.g. SLURM);
- Experience working with genetic analyses (e.g., GWAS, rare variant analysis, etc) and / or genomic data from different modalities (DNA sequencing, RNA-seq, proteomics, DNA accessibility assays, etc.).


Benefits at insitro
- Excellent medical, dental, and vision coverage
- Open vacation policy
- Team lunches (catered daily)
- Complementary onsite barista and snacks 
- Commuter benefits
- Paid parental leave
- Flexible work schedule (on site and remote)

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.