Staff/senior Software Engineer, Machine Learning Platform (ad Cloud)

Appier

Tokyo, Japan
Not specified; not specified; not specified
On-site
Spark and flink pipeline architecture
Kubernetes and argo workflows experience
Python or java coding proficiency
Appier is seeking a Staff/Senior Machine Learning Platform Engineer to join their team in Tokyo, Japan. The position involves designing and scaling machine learning infrastructure and requires strong coding skills in Python and/or Java, along with experience in data systems and platform engineering

Job Summary

  • The role involves shaping the architecture of an ML platform that powers end-to-end infrastructure for model training, evaluation, deployment, and monitoring at scale.
  • Candidates will design robust job execution frameworks and maintain internal API servers to orchestrate ML jobs on Kubernetes using tools like Argo Workflows and Terraform.
  • The team actively champions best practices by adopting LLM-based tools such as GitHub Copilot to accelerate development, documentation, and debugging processes.

Matching Summary

Match Score: 85

Appier is seeking a Staff/Senior Machine Learning Platform Engineer to join their team in Tokyo, Japan. The position involves designing and scaling machine learning infrastructure and requires strong coding skills in Python and/or Java, along with experience in data systems and platform engineering.

Salary

Not specified; Not specified; Not specified

Skills & Requirements

Must-have

  • Spark and Flink pipeline architecture
  • Kubernetes and Argo Workflows experience
  • Python or Java coding proficiency
  • ClickHouse and PostgreSQL management
  • Prometheus and Grafana monitoring

Nice-to-have

  • LLM-based programming assistant adoption
  • Mentoring junior engineers
  • Cross-functional collaboration skills
  • Infrastructure-as-code expertise
  • Developer tool creation

Key Requirements

  • Bachelor's degree in Computer Science or related field
  • 4+ years of hands-on experience in data systems
  • Master's degree preferred
  • Experience with large-scale production systems

Work Rights

Not specified

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