Machine Learning Engineer – Customer Data Platform Section, Analytics Data Full-time

Job Description:

Business Overview

Rakuten group has almost 100 million customer base in Japan and 1 billion globally as well, providing more than 70 services in a variety such as ecommerce, payment services, financial services, telecommunication, media, sports, etc.

AI Success Supervisory Department (AISSD) provides various solutions by leveraging Rakuten group’s data. The department has international culture created by excellent employees joined around the world and provides the cutting-edge data science. Following the strategic vision “Rakuten as a data-driven membership company”, AISSD is expanding our data activities across our multiple Rakuten group companies.

Department Overview

Customer Data Platform Section provides the platform to realize ‘Digital Twin’. With hundreds of millions of members and trillions (Japanese Yen) in spending, Rakuten’s Membership enjoys an un-paralleled eco-system of benefits and is amongst the largest in the world. Our talented and driven team operates a portfolio of products and services that optimize Rakuten membership experiences using data.

You’ll benefit from our network of global communities and collaborative culture that will help you build technical and functional skills and capabilities. And because we serve more than 28 countries industries globally, you’ll have the opportunity to develop valuable industry-specific expertise.

The scale of our capabilities and client engagements and the unique way we innovate, operate and deliver value will give you the opportunity to deepen your existing skills even as you help create the latest technology trends. You’ll have access to leading-edge technology.

Position:

Why We Hire

We are looking for a someone with a problem-solving attitude to build and maintain model deployment pipelines enabling state-of-the-art AI-solutions. A T-shaped engineer with the ability to adapt and the passion to get things done and deliver results.
You will have the chance to own pipelines empowering our businesses and make tangible contributions. You will be working and exchanging knowledge with a global team of talented engineers.

Position Details

– Build and maintain ML deployments and Data Pipelines

– Build data APIs and ML microservices

– Utilize machine learning frameworks and libraries to build ML Solutions

– Work with new technology, and bringing innovations into our services

– Collaborate globally with other team members

Mandatory Qualifications:

– 5+ years of development experience, preferably using python

– Able to write production level code, which is well-written and explainable

– Experience using common machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, NumPy, pandas)

– Experience with public cloud (e.g., GCP, AWS, AZURE), Databricks Platform

– Experience with deployment and training of Machine Learning models and MLOps tooling (MLFlow, Seldon, etc…)

– Experience with RESTful API and batch applications

– Experience with full development lifecycle, agile development, using task management tool like JIRA

– Microservice development and operation experience with Docker and Kubernetes

– Experience with big data technologies such as Spark, Kafka, Delta Lake etc.

Desired Qualifications:

– Experience in handling Data Modelling, Data & Model-Observability

– Experience with production engineering practices such as CI/CD

– Experience with performance profiling and tuning

– Experience with developing distributed, scalable and high-available applications

– Knowledge about applications using GPU, Machine Learning, Deep Learning

– Experience working with orchestration tools (airflow, kubeflow, etc)

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