- Research, design, and build machine learning systems for prediction, recommendation, and automation
- Execute the key phases of the ML lifecycle including data extraction, exploratory data analysis, data preparation, model development and training, model evaluation and validation, and model serving
- Build monitoring tools and pipelines for automated training and deployment
- Collaborate with data scientists, data engineers, product managers, and stakeholders to build robust production systems
- Bachelors in a quantitative field such as Computer Science, Mathematics, Statistics, Machine Learning, or equivalent
- More than three years of experience as a data scientist, machine learning engineer, or equivalent role
- Experience in at least one primary language (e.g., Java, Scala, Python) and SQL (any variant)
- Experience in one or more machine learning frameworks such as TensorFlow, PyTorch, Theano, etc.
Nice to haves
These aren’t required, but be sure to mention them in your application if you have them.
- Masters or PhD in a quantitative field such as Computer Science, Mathematics, Statistics, Operations Research, Machine Learning, or equivalent
- More than five years of experience as a data scientist, machine learning engineer, or equivalent role
- Experience building and maintaining microservices
- Experience with Big Data technologies like BigQuery, Spark, Hadoop, AWS Redshift, Kafka, or Kinesis streaming
- Experience with AWS services such as Glue, SageMaker, Athena, and S3
- Extensive knowledge and work experience in recommendation systems, deep learning, NLP, and optimization
- Experience maintaining data security and privacy
- Expertise in MLOps frameworks, CI/CD pipelines, and automation
9 to 12 million JPY annually.