
Staff machine learning engineer, app ads modeling
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Meliora Therapeutics
·11 days agoMeliora Therapeutics
·11 days agoLocation
remote, United States
Salary
$90k/yr
Commitment
Full Time
Level
Junior (<2 years)
Biotech is on the verge of a revolution. Breakthroughs such as the advent of CRISPR and systems for fast and efficient multi-omic sequencing in combination with structural advances in machine learning are unleashing the ability to interrogate human biology in unprecedented ways. A key initial goal of Meliora Therapeutics’ computational engine is to develop a robust, multi-modal MOA atlas for cancer drugs. This atlas will consist of 21st century phenotypic “molecular fingerprints” of different mechanisms of action, and will serve as a reference library that can be used to characterize new molecules of interest. Our platform has already surfaced a number of interesting candidate drugs with promising laboratory validation and we are looking for world class talent to expand and deepen the capabilities of this advanced computational engine using the latest ML approaches, making an impact on cancer in the process.
The founding team includes CEO David Li (1st business hire at Benchling, GS, KKR, Penn Life Sciences and Management), Dr. Jason Sheltzer (Faculty at Yale School of Medicine, Presidential Early Career Award, Forbes 30u30), Joan Smith (Sr. Staff engineer at Google, MIT Physics), and Zach Owen (Data Scientist Tech Lead at Verily, previous ML startup technical co-founder, MIT PhD). We are backed by leading funds including BrightEdge, VillageGlobal, HOF Capital, Obvious and others.
Machine learning team members play an important role in developing the core algorithmic engine of a next-generation biotechnology company, and so we are looking for people who delight in being multi-disciplinary, seek excellence at every turn, and have an unyielding desire to continuously learn and share knowledge. If this sounds like you, we would love to speak with you.
What you’ll do:
Background and skills we are looking for:
What we offer:

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