Rakuten Group, Inc. is the largest e-commerce company in Japan and the third-largest e-commerce marketplace company worldwide. Rakuten provides a variety of consumer and business-focused services, including e-commerce, e-reading, travel, banking, securities, credit card, e-money, portal and media, online marketing, and professional sports.
AI Engineering Supervisory Department, under the Tech Division, leads the transformation of Rakuten by commercialization of Artificial Intelligence, Cognitive Computing, and Machine Intelligence Technologies for Rakuten businesses.
With access to Rakuten’s ecosystem of more than 70 services, global businesses, and technology expertise across Asia, Europe, and the Americas, IDX – Insights and developer experience is to create tools and technologies to support experimentation, insight creation, tool creation, and ML Serving. One example of what we are working on is embedding deep learning models over GPU serving at scale for various important AI initiatives. Tools team works on creating data validation/model validation tools, model evaluation tools, etc
Why We Hire
We are looking for someone with a problem-solving attitude to build and maintain model deployment pipelines enabling state-of-the-art AI products/tools. A T-shaped engineer with the ability to adapt and the passion to get things done and deliver results.
- Build and maintain ML deployments pipelines on GCP and Internal Cloud
- Deploy complex architecture and network configuration to minimize latency in the current systems.
- Develop pipelines for continuous operation, feedback, and monitoring of ML models leveraging best practices from the CI/CD vertical within the MLOps domain
- Optimize AI development environments (development, testing, production) for usability, reliability, and performance
- 6+ years of development experience, preferably using Python, Go, and C++
- Able to write production-level code and documentation
- Experience working with GPUs to develop and deploy models
- Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have
- Hands-on experience building CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Airflow, or similar tools is a must-have
- Either CKA or CKAD
- Experience with full development lifecycle, agile development, using task management tools like JIRA
- Certified Google Cloud Architect or equivalent on other other clouds
- Experience with datastores such as Redis, Postgres, Couchbase, load balancer, HAProxy, Nginx, etc. Good knowledge of DevOps process and principles
- Experience with log analysis systems such as Prometheus, InfluxDB, Grafana ElasticSearch/Kibana, etc.