Java & Machine Learning Engineer (in Tokyo) (вакансія неактивна)

Software Engineer with Java/Scala

Do you want to do impactful work that will be deployed to millions of citizens weekly? Do you want your input to be heard and taken into consideration? Apply and create a digital future with us!

• Up to 45 — 60 000 USD net per year
• B2B long-term permanent contract
• Direct employment by the client
• Professional equipment provided
• Move to Japan and work in the heart of Tokyo!

We are looking for a Junior/Mid Software Engineer for a Silicon Valley-based startup focused on full-cycle Machine Learning and Data Science automation. Their platform automates the entire process of building predictive models starting from raw business data through data and feature engineering to machine learning all the way to production.

Requirements

• Well-structured knowledge of software design, implementation, and testing in Python and Java/Scala (or any typed language such as C++)
• 2+ years of enterprise-grade software development experience
• Great knowledge of DevOps platforms such as Jenkins, GitHub, JIRA, etc.
• Basic knowledge about data analytics, machine learning, statistics, or relevant areas (e.g. learned with online courses)
• Strong English communication skills

Nice to have

• Experience working in a startup environment
• Experience in software development in Agile and Scrum
• Experience in architecture designs by object-oriented programming and/or functional programming
• Experience with cloud platforms such as AWS (EC2, EMR, etc.), Azure, GCP
• Experience with the Hadoop ecosystem (Spark, Yarn, HDFS)
• Experience in Docker and Kubernetes
• Experience with building data analysis pipelines, distributed computing and big data analytics

Responsibilities

• Develop the client’s product with the Agile development manner: requirement analysis, architecture design, implementation, unit/integration testing, end-to-end testing, and technical support of the product.
• Use Python for the user-interface codes
• Use Scala for business logic and interfaces with the client’s core engines
• Use Spark and Hadoop as core libraries