Research Engineer

SyntheticGestalt Shinjuku-ku, Tokyo
  • 💴 No salary range given
  • 🏡 Partially remote
  • 🧪 2+ years experience required
  • 💬 No Japanese required
  • 🗾 Japan residents only
  • 🧳 No relocation support

About SyntheticGestalt

SyntheticGestalt Shinjuku-ku, Tokyo

An AI startup specialising in the life science area. Focused on drug discovery and enzyme discovery with advanced machine learning models. Collaborating with research groups in prestigious universities in the UK and Japan, supported by large-scale grants.

Key benefits

  • International team
  • Office surrounded by nature
  • Flextime

About the position

SyntheticGestalt seeks to develop autonomous systems to invent new drug candidate compounds for patients suffering from diseases, and new genes for synthetic organisms that will improve the global environment. As a Research Engineer, you will define and implement the steps necessary for the successful development of such a system. Specifically, you will develop the machine learning models that compose the system, which will be difficult as they differ from the typical models in terms of the data and their purpose. You will be required to propose, with the help of members with various specialisations, hypotheses on what improvements would bring you closer to achieving your objectives, and to act as a pioneer in actually implementing and verifying these hypotheses.

The development of machine learning systems at SyntheticGestalt consists of teams that take on various roles, e.g. developing models for the generation of compounds, developing models for predicting protein function, searching for new training data, designing features for small molecule compounds, etc. Your interests and aptitude will determine the team you belong to and your area of focus, but you will often collaborate with other teams. This is where the real thrill of working together to develop one system for a long time for shared objectives comes in.


All of the following are areas of responsibility, but one of them will be a dedicated area depending on the team belonging to.

  • Develop a machine learning model dealing with chemical compound information, propose hypotheses to improve the model, validate the performance of it.
  • Propose and create new features based on data and purpose
  • Implement MLOps and distributed computing environments
  • Explore and add data to be used for training and inference
  • Search for relevant papers, apply and validate their concepts


We have different requirements depending on whether you’ve worked with chemical compound information or not.

If you have experience working with chemical compound information, we’re looking for

  • 2+ years of working experience as a machine learning engineer or a data scientist working with chemical compound information
  • 1+ publication in an international conference / journal as a first author

If you have a general background in machine learning, we’re looking for

  • 4+ years of working experience as a software/machine learning engineer
  • 3+ years of working experience as a machine learning engineer
  • 2+ year of working experience as a deep learning engineer
  • 1+ year experience of each in developing 2+ types of deep learning models: e.g., image 1yr and natural language 1yr, or graph 1yr and generative model 1yr

Nice to haves

These aren’t required, but be sure to mention them in your application if you have them.

  • PhD in computer science, mathematics, physics, or a related field
  • Experience in Chemoinformatics, Bioinformatics or a related field
  • Experience in distributed computing / high performance computing
  • Experience in cloud computing
  • Working experience as a data scientist

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