*Please note - this posting is for future opportunities and we will contact you should an opportunity arise that may be a good match.
Machine learning lies at the core of insitro’s approach to rethinking drug development. As a machine learning engineer, you will lead the development of cutting edge machine learning methods that solve key problems in the drug development process. You will work closely with a cross-functional team of life scientists, bioengineers, and data scientists to identify areas where machine learning can make a difference, to conceptualize and develop biological datasets using cutting edge, high throughput platforms, and to analyze these data sets using the best machine learning methods, applied at scale. You will need to come up with novel methods that use a broad spectrum of machine learning approaches, including techniques at the forefront of the field. We aim to develop large data sets, and apply cutting edge machine learning methods; hence, you will need to develop and deploy machine learning methods at scale. You will work as part of a team to rigorously analyze our data, pull out key insights, and make accurate predictions that will let us quickly develop drugs that have high efficacy and low toxicity. You will be joining as the founding team of a biotech startup that has long-term stability due to significant funding, but yet is very much in formation. A lot can change in this early and exciting phase, providing many 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!
Nice to Have
Experience in these areas is highly valued but not required
Benefits at insitro
insitro is a data-driven drug discovery and development company using machine learning and high-throughput biology to transform the way that drugs are discovered and delivered to patients. The company is applying state-of-the-art technologies from bioengineering to create massive data sets that enable the power of modern machine learning methods to be brought to bear on key bottlenecks in pharmaceutical R&D. The resulting predictive models are used to accelerate target selection, to design and develop effective therapeutics, and to inform clinical strategy. insitro was launched in 2018 with a Series A of $100M funded by top investors including a16z, Arch Venture Partners, Foresite Capital, GV, and Third Rock Ventures. In 2019 the company announced a collaboration with Gilead Sciences in the area of NASH, a collaboration with BMS in the area of ALS, and in mid 2020, announced a Series B financing of $143M including current investors and new investors Canada Pension Plan Investment Board (CPP Investments), T. Rowe Price, BlackRock, Casdin Capital and other leading investors. The company is located in South San Francisco, CA. For more information about insitro, please visit the company’s website at www.insitro.com
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