Bioinformatics Engineer, Algorithms

Mountain View, CA /
Bioinformatics /
Deepcell is an early-stage Stanford spin-off company that has developed a unique platform for use in research, diagnostic testing, and therapeutics. We combine microfluidics, imaging, deep learning, and genomics to identify, isolate and analyze live, single cells. Our technology addresses diverse applications in the life sciences.

Come join Deepcell and make a difference! We're a small team of passionate innovators in biomedical engineering, artificial intelligence, molecular biology, and genomics. Our technology has won multiple prestigious awards and is backed by top-tier venture capitalists in Silicon Valley. 


Bioinformatics is an essential component of Deepcell’s technology. You will develop workflows for the analysis of transcriptomic and genomic data for multiple applications, employing standard tools and developing novel algorithms where needed. You will integrate single-cell omics data with Deepcell’s proprietary morphological profiling technology. You will work in close collaboration with engineering, software, biology, and data science teams on new product features and external collaborations.

Minimum Qualifications

    • MS or Ph.D. in computational biology, another analytical discipline, or equivalent industry experience
    • 5+ years experience developing algorithms for the analysis of large genomic and/or transcriptomic and proteomic datasets
    • Deep familiarity with the concepts, standard tools and data in bioinformatics, genomics and NGS technology
    • Strong understanding of and experience with statistical and machine learning methods 
    • Proficiency in Python and associated numerical libraries
    • Well versed in rigorous software engineering practices and discipline: code reviews, version control, etc. 
    • Passion for solving problems and for developing novel applications in biotechnology and medicine
    • Effective communication with engineers and scientists from different disciplines

Preferred Qualifications

    • Experience with software development in a clinical/regulated environment.
    • Experience with deep learning techniques and tools