Lead, Machine Learning Engineering
2 weeks ago
At 1910 Genetics, we first establish an understanding of the molecular basis of disease to the granularity at which the world understands sickle cell anemia. This understanding centers biology as our North Star and drives our integration of artificial intelligence (AI), computation, and biological automation to accelerate the design of small molecule and protein therapeutics.
Recent advances in computational technologies have placed historically “undruggable” targets within therapeutic reach. But at 1910 Genetics, we often say “Biology is King,” meaning that computational technologies are only impactful in drug discovery when driven by experimental biology. Our platforms’ scale and breadth empower us to be therapeutic area-agnostic with programs ranging from neuroscience and immunology to infectious disease and oncology, to name a few.
You are someone we can count on to...
Act as both an Individual Contributor (IC), who can roll up her sleeve, and play an important role in our mission to use AI/ML to develop drugs against historically difficult disease targets, as well as a Leader who can build and grow the ML Engineering & AI Research team over time
Your key responsibilities will include…
- Own
- Propose innovative AI/ML models that address specific use cases in our drug discovery process
- Develop and launch prototype models
- Productionize AI/ML models on AWS
- Own the company’s AWS Infrastructure
- Grow the team
- Teach
- Teach their cross-disciplinary colleagues from Computational Chemistry, Medicinal Chemistry, Computational Biology, Cell Biology, and Pharmacology, how AI/ML can solve important problems for them
- Learn
- Drug discovery and development
- Improve
- Our existing process for incorporating AI/ML into drug discovery
- Form a view on which AI/ML models address the highest need use cases
- in our drug discovery process
- Begin prototyping AI/ML models on AWS
- Productionize AI/ML models on AWS that would become a cornerstone of the company’s drug discovery efforts
- Continue improving the first set of production-grade AI/ML models on AWS
- Build and productionize improved AI/ML models on AWS to harmonize, and accelerate our drug discovery process
- Grow the team with new hires including ML Engineers, AI Researchers, and Product Managers
- Extremely generous equity package coupled with competitive salary
- Healthcare benefits
- Generous vacation and parental leave
- Super cool team building activities
- Flexible work schedule
- Great colleagues
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