Machine Learning Research Scientist/Engineer, Atomwise
AI/ML for Drug Discovery
$175-260k
+ Stock compensation plan
AI systems for drug discovery
Job no longer available
AI systems for drug discovery
21-100 employees
Job no longer available
$175-260k
+ Stock compensation plan
21-100 employees
Company mission
To make better medicines, faster.
Role
Who you are
- Ph.D. in Computer Science, Machine Learning, Computational Chemistry, Bioinformatics, or a related field
- Hands-on experience with graph neural networks, multi-task learning, active learning strategies, multi-objective optimization, and generative modeling, in particular their application to problems in small molecule drug discovery
- Proficiency in designing and implementing novel machine learning architectures in PyTorch
- Strong problem-solving and analytical skills, with a demonstrated ability to conduct independent research
- Experience with collaborative software engineering and developing high quality, maintainable code in a large codebase
- Demonstrable communication and collaboration skills
- A strong publication record in relevant conferences and journals is highly desirable
- Experience with 3D generative modeling and knowledge of protein-ligand interactions is a plus
- Experience in optimizing models for large-scale training and inference is a plus
- Familiarity with cheminformatics tools and libraries (e.g., RDKit) is a plus
What the job involves
- We seek a highly motivated and creative Machine Learning Researcher to join our growing team. You will be at the forefront of developing and applying advanced machine-learning models to accelerate the discovery of novel therapeutics
- Your work will directly impact the development of innovative AI-driven drug discovery platforms. This role offers the opportunity to work on challenging problems at the intersection of machine learning, chemistry, and biology, with access to extensive datasets and state-of-the-art computational resources
- Develop and implement novel deep learning models for molecular property prediction, design and optimization, and virtual screening
- Design and execute experiments to evaluate the performance of generative models in generating chemically valid and biologically relevant molecules
- Collaborate with cross-functional teams of chemists, biologists, and software engineers to integrate ML models into drug discovery pipelines
- Conduct in-depth analyses of model outputs and performance metrics to identify areas for improvement
- Stay up-to-date with the latest advancements in machine learning and computational chemistry, and contribute to the scientific community through publications and presentations
- Contribute to the development of scalable and efficient machine learning infrastructure by productionizing research for at-scale use by drug discovery teams
- Explore and implement innovative techniques for multi-objective optimization, property prediction, and active learning within the context of generative modeling for drug design
Our take
AI has become a critical tool to advance the pace and complexity of new drug discovery. It’s an emerging sector that’s attracted steep VC investment, with different startups applying the technology to different areas of pharmaceutical research. Preclinical pharma company Atomwise is focusing on structure-based small molecule discovery.
Focusing on more than 600 disease targets with 250+ global partners, the company has already had success. It’s also developing a wholly-owned drug discovery pipeline in co-development with X37, and partners with biopharma companies like Bayer and GC Pharma and researchers at institutions like Toronto and Duke universities.
The emerging, urgent, and relatively specialist sector of AI assisted discovery has made for a cash rich and relatively non-competitive market. Terray Therapeutics, Owkin, and Hoxton Ventures are just a few of the startups using varying methods in varying areas of pharma specialisation, all of which are raking in hundreds of millions in VC investment. So there’s a lot to play for, and Atomwise has carved out a strong and leading niche for itself that lays a strong foundation for future growth
Kirsty
Company Specialist at Welcome to the Jungle
Insights
-31% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Oct 2020
$2.3m
GRANT
Aug 2020
$123m
SERIES B
Total funding: $176.7m
Company benefits
- Competitive salary, commensurate with experience
- Stock compensation plan – you’ll be an Atomwise co-owner
- Platinum health, dental, and vision benefits
- 401k with 4% match
- Flexible work schedule
- Generous parental leave
- Strong emphasis on collaborative learning and career development
Company HQ
Yerba Buena, San Francisco, CA
Leadership
Izhar Wallach
(Co-Founder & CTO)Worked as System Admin at Intel, then an Algorithm Developer at Keddem Bioscience Ltd., before completing a Computer Science PhD at the University of Toronto.
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