Full stack engineer
- Silicon Valley, CA, United States
- Menlo Park, CA, United States
- $135k - $190k
- 0.03% - 0.12%
- Google Cloud
Interested in helping to develop cutting edge technologies to empower cell biology and save lives? If so, we'd love to talk to you!
Our company is focused on developing a new technology to improve biological research and, ultimately, health outcomes, across all of biology, enabling previously impossible applications. We deliver detailed breakdowns on a cell-by-cell basis, by using deep learning to classify cells based on their morphology. We've launched an internal product and are working to develop a commercially releasable version.
Come join Deepcell and make a difference! We're a rapidly growing team of stellar innovators in biomedical engineering, artificial intelligence, and molecular biology. Our technology has won multiple prestigious awards and is backed by top-tier venture capitalists in Silicon Valley including Andreessen Horowitz and Bow Capital.
As a Full Stack Software Engineer you will design and develop web tools to explore and navigate rich cellular data. Academic and industrial researchers will use your tools every day to do cutting edge research! You’ll need to build usable and high performance web applications to help them manage and make sense of large, complex data sets.
Additionally, you will design and develop our SaaS platform which enables researchers to manage their experiments, run machine learning models, evaluate its performance and explore the rich sets of biological data. You’ll build maintainable and performant APIs and data pipelines to enrich and interact with data from close to a billion cells.
You’ll work in an interdisciplinary team composed of data scientists, bioinformaticians, biologists and software engineers to help solve hard problems which improve biological research and, ultimately, health outcomes, across all of biology.
Deepcell is combining advances in AI and single-cell analysis to develop an automated platform for use in translational research, diagnostic testing, and therapeutics. The company’s unique, microfluidics-based tool uses an iterative AI-powered approach to classify cells based on detailed visual features and sort them without inherent bias. Unlike other approaches, the Deepcell platform can maintain cell viability for downstream characterization and can be used to isolate any type of cell, even those occurring at frequencies as low as one in a billion.
In one word, we treasure cautious optimist attitude. Optimism alone may result in too much disappointment and too much caution does not get anything done.
- Google Cloud
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