Join our team.
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.VIEW MORE
We are looking for
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.VIEW DETAILS
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.VIEW DETAILS
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.VIEW DETAILS
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.VIEW DETAILS
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?
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.
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.
Support participation in various global conferences, media/research/journal support for knowledge enhancement
Support internal SIG(Special Interest Group)s
Support participation in AI/Industrial competition, voluntary community works, and more