Help us speed up the drug discovery process!

As is now self-evident due to the on-going pandemic, the drug discovery process is too slow. One of the key roadblocks lies in synthesis planning — designing how to make a molecule selected as a potential drug candidate.

Molecule.one is on a mission to speed up the drug discovery process by rapidly designing reliable synthesis pathways using artificial intelligence. In other words, we tell chemists how to make molecules they want to make.

Our product is already used by the first customers from the pharmaceutical and biotech industry. To learn more about the technology, please listen to our Warsaw.ai presentation for a high-level overview, or check out one of our papers for a deeper dive into our research. You may also read about us in TechCrunch or Forbes (in Polish).

If you want to join a world-class team in applying state of the art technology to make the drug discovery process faster, this offer is for you.

What will you contribute?

As a machine learning engineer, your responsibilities will include:

  • Designing and implementing state-of-the-art machine learning and artificial intelligence solutions
  • Following relevant literature
  • Contributing to the shape of our long-term strategy and the direction in which we develop our product
  • Writing research papers and working in scientific collaborations

What technology will you work with?

In analogy to AlphaGo, we find the synthesis plan using a search algorithm coupled with state-of-the-art deep neural networks for predicting outcomes of chemical reactions. We use artificial intelligence and deep learning in a novel application area, which requires integrating many perspectives and designing novel solutions.

For machine learning, we primarily use Python, PyTorch, and AWS. The rest of the technological stack includes Docker, Rust, JavaScript, Node, React, and Postgres.

What team will you be joining?

You will be reporting to Stanisław Jastrzębski, our Chief Scientific Officer, and work along with our machine learning team. Your role will be uniquely interdisciplinary. As such you will also regularly discuss and interact with the rest of the team to align your work with the broader drug discovery context and customer needs.

Required

  • In-depth understanding of foundations of machine learning and deep learning
  • Equivalent of minimum one year of experience in applying and developing deep learning solutions. We are particularly interested in a demonstrated ability to conceptualize a problem and pick the correct approach using deep learning.
  • Strong programming skills (including but not limited to versioning control system, testing, design)
  • Knowledge of algorithms, statistics, linear algebra
  • Problem identification, problem solving, critical thinking, independence in designing solutions
  • Ability to work in a team in a fast paced environment (including but not limited to agile methodologies)
  • Willingness and ability to quickly grasp new concepts in organic chemistry, drug discovery, and artificial intelligence
  • Communicative English (B2)

Nice to have

  • Additional background in chemistry or biology
  • Experience in research (for example published work, PhD degree)
  • Knowledge of technologies such as AWS, Docker

Offer

  • 10 000 - 20 000 PLN net (B2B) depending on your experience.
  • Possibility of remote work (with regular in-person meeting after the pandemic)
  • Office in Warsaw in the city center
  • Funding for conferences and workshops
  • Opportunity to publish and present your work at top venues
  • Paid vacation leave (for B2B as well)
  • Great colleagues
  • The working gear that you choose
  • Employment Stock Ownership Plan -- you will co-own Molecule.one

Would you like to make the drug discovery process faster with us? Please reach out with your CV and any other materials (github, papers, blog, etc) to [email protected]

We are looking forward to meeting you!

Author

Published

Stanisław Jastrzębski