VantAI is building a computational pipeline that combines state-of-the-art physics-based modeling and machine learning to revolutionize drug discovery and development.
The company collaborates with leading biopharmaceutical companies to design, test, and optimize novel therapies for difficult diseases.
The AI Scientist will join the machine learning team to develop an advanced pipeline for designing proximity-inducing molecules.
This role involves working with a team of machine learning engineers on unsolved problems related to representation learning of proteins, small molecules, biological networks, and genomics.
Key responsibilities include scientifically directing the design and training of large-scale Deep Learning systems, developing novel architectures and training paradigms, collaborating with content experts from various domains, and contributing to top-tier ML conferences and journals.
Requirements:
A MS/PhD degree in Computer Science, Statistics, Applied Mathematics, Computational Biology, Computational Chemistry, or a related subject is required; BS degrees may be considered for highly qualified candidates with significant work experience.
A track record of contributing to novel methods for state-of-the-art Deep Learning, including experience with large-scale Transformers, Graph Neural Nets, and ConvNets.
A minimum of 2 years of experience on machine learning teams, ideally in a start-up environment.
At least 4 years of ML research experience in industry or academia, with strong familiarity with PyTorch.
Proficiency in Python is required.
Relevant experience working in a Linux/UNIX environment with basic data engineering and scripting abilities is necessary.
The ability to understand business problems and build models that drive value while prioritizing research efforts is essential.
Strong communication skills to convey modeling setup and results at various levels of abstraction are required.
Benefits:
The salary range for this position in NYC is $180,000 - $200,000.
The company is open to discussing higher salaries for more experienced candidates during the initial conversation.