Join our team.

Job openings

At MakinaRocks, we are looking for computer scientists, mathematicians, physicists, and engineers. Our interdisciplinary team is closely associated and works together to tackle unique data challenges that our clients face.


We are looking for

  • Data Scientist

    Data Scientist offers solutions for improving manufacturing and industry productivity and efficiency by analyzing industry data, modeling and implementing models in a variety of quantitative ways, including Machine Learning, Deep Learning and Statistics.

  • ML Research Engineer

    ML Engineer conducts research and development to implement and apply the latest machine learning techniques and algorithms to solve practical problems in the industrial field. We also develop an analysis and modeling platform to improve the data analysis process.

  • Backend SW Engineer

    Back-end Software Engineer designs and implements software to effectively apply the latest machine learning techniques and algorithms to the real world. To this end, we build a platform and infrastructure to streamline analysis and modeling.

  • Frontend SW Engineer

    Front-end Software Engineer designs and implements software that makes it easy to use the latest machine learning techniques and algorithms in the real world. To do this, we try to develop front-end solutions that meet our clients’ needs.

  • Business Development

    At MakinaRocks, we are seeking Business Developers who can find and grow potential AI business opportunities both in the conventional industrial setting and in the new digital environment. The Business Developer should be an active listener with excellent interpersonal skills and have a passion to chase and close new business from cold calls to inbound requests of diverse clients.

Things that keep us awake at night are questions such as

  • How to overcome ‘catastrophic forgetting’ in neural networks when implementing a ML system that continuously learns?
  • How to enable a Deep Learning model to learn from related tasks (i.e., Transfer Learning) while dealing with the lack of data? Are the techniques in Transfer Learning applicable to numeric data?
  • How to build an interpretable model using techniques in Explainable AI (XAI) that can connect to subject matter expertise?
  • How to apply agile to Data Science? If not all, which agile methodologies fit?

Our values

Intelligent confidence

We are confident in what we do, and there is no limit to what we are capable of.


We actively encourage and embrace opinions from all members.


We leverage our experience and knowledge of AI to grow together with our clients.

Grow together

We believe that personal growth is directly related to our company’s growth.
To accomplish this, we support all members with various opportunities to learn and grow.

  • Growth

    Support participation in various global conferences, media/research/journal support for knowledge enhancement

  • Membership

    Support internal SIG(Special Interest Group)s

  • Inspirational Opportunities

    Support participation in AI/Industrial competition, voluntary community works, and more

Have you got any questions?

Write us.