You will
- Drive speed and accuracy improvements in our ML platform, coming up with architecture modifications for 2D and 3D graph neural networks, and rapidly implementing and testing them in PyTorch
- Keep up with deep learning research, especially pertaining to graph neural nets and graph generative models, and quickly prototype ideas gleaned from the literature
- Dive deep into molecular datasets, creating statistically rigorous train, valid, and test sets to optimally train our models for real-world prediction and generation tasks
- Develop creative featurizations of 2D and 3D molecular structures that are inspired by laws of physics and chemistry, enabling our networks to take better advantage of available data
- Work closely with software engineers and medicinal chemists to make our ML platform maximally adaptive to different use cases
You are
- A strong software engineer who will write code quickly and uphold our code quality standards
- Comfortable with linear algebra and statistics
- Experienced applying traditional ML techniques and/or deep learning to real-world problems
- A deep thinker who reasons from first principles over pattern matching
- Interested in learning about machine learning, biochemistry, and the drug development process
What we offer
- The opportunity to work on challenging, high impact ML research that is immediately deployed to accelerate the discovery of new medicines
- Strong technical coworkers in AI, software, and chemistry, who all have a powerful mix of intellectual curiosity and humility. The team reads and discusses 1-2 ML or chemistry papers every week to stay on top of the field and inspire new ideas
- Competitive salary and equity. Medical, dental, and vision insurance, and a 401(k) program
0 applies
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