Responsibilities
- Appropriate design of evaluation methods based on task-specific understanding of metric properties
- Hypothesis proposal, development implementation and performance validation of machine learning models for compound information
- Proposal and creation of features according to data and purpose.
- MLOps, implementation of distributed computing environments
- Training machine learning models, exploring and adding data to be used for inference
- Search for relevant papers, application and validation of concepts
Requirements
- Empathy with mission, vision and values
- 6+ years’ experience working as a software/machine learning engineer
- 5+ years’ experience as a Machine Learning Engineer
- 4+ years’ experience as a Deep Learning engineer
- Experience in developing GNN or generative models or Geometric Deep Learning
- At least 2 publications as first author in international conferences/ journals
- Experience in continuous delivery of machine learning models to the business
- Leadership experience in developing a team of 4 or more people
- Ability to formulate and specify mathematical algorithms
Nice to haves
While not specifically required, tell us if you have any of the following.
- PhD in computer science, mathematics, physics or related field
- Experience in cheminformatics, bioinformatics or related fields
- Experience in distributed computing/high performance computing
- Practical experience as a data scientist
- Kaggle Master or Ground master
Compensation
10 to 15 million JPY annually.
