Contribute to building scalable backend systems and participate in service operation activities to ensure reliable and high-performing distributed services.
About this role
Appier hires a Staff or Senior Machine Learning Platform Engineer for the Ad Cloud team in Tokyo. Its Machine Learning Platform Team runs end-to-end infrastructure for model training, evaluation, deployment and monitoring, with hundreds of models executed daily over billions of data records in batch and streaming pipelines.
The engineer shapes the platform's architecture and core components: batch pipelines in Spark, streaming in Flink, job orchestration with Argo on Kubernetes and infrastructure tools. The work includes designing and running ML job execution frameworks for training, inference and post-processing, building internal API servers and tools to orchestrate ML jobs on Kubernetes and running data infrastructure on ClickHouse and PostgreSQL with Prometheus and Grafana.
Applicants need a bachelor's degree in computer science, engineering or a related field and four or more years in data systems, machine learning infrastructure or platform engineering. They need strong Python or Java, practical experience with Spark, Flink, Kubernetes and infrastructure as code, ClickHouse or PostgreSQL, understanding of ML pipelines, and the ability to lead cross-functional platform projects. Applying LLM tools such as Claude Code to raise productivity is expected.
This is an AI-generated summary of the employer's original posting — details can be incomplete, out of date or simply wrong. Always confirm everything on the official posting before applying.
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