We at Platform team provides the services, tools, and knowhow to make the Business units operationally independent. The domains we cover are Android/iOS core development and CI/CD, Data Platform providing analytics as a service, and back end core development and Infrastructure.

The role

As a Site Reliability Engineer - Machine Learning Operations (ML Ops), you'll be part of Platform-Infrastructure team which provides support on application development, designing, managing and maintaining infrastructure services over the course of their life cycle, contributing operations and development knowledge to solve problems dealing with complex infrastructure to improve performance, visibility, stability, availability and reliability using codified, scripted, or automated solutions. Responsible for ML specific resources within the infrastructure.

What we expect

• Programming experience in at least one modern programming language, Go (Java/Scala is a plus).
• 5+ years of programming and system administration on Linux environments, preferably working on high throughput and low latency systems.
• Extensive experience with Public Cloud platforms (preferably GCP).
• Extensive experience with Kubernetes, Ansible and/or Terraform, Kafka
• Experience in ML operations.
• Excellent understanding of distributed system design across process and site boundaries
• Hands-on experience with service orchestration and management, deployment activities, configuration management, and all necessary automation
• Good understanding of process isolation, virtualization and containerization concepts and being able to apply them when necessary
• Good understanding of software development lifecycle, versioning, building, testing, staging and deployment processes with a strong continuous delivery mindset
• Having a research-oriented mindset
• Strong tendency to keep things simple and maintainable (stick to KISS + YAGNI)
• Experience in configuring ,provisioning and maintaining high performance clusters
• Experience to create and maintain lifecycle for the ML models.

What you'll work on

• Building tooling to ease the provisioning and scaling of infrastructure resources.
• Continuously improve and extend infrastructure components to handle growth.
• Describe the role as split between Data Platform and Core Infrastructure
• Optimize overall systems performance and investigate production issues for future improvements.
• Ensure systems availability, reachability, maintainability, and testability.
• AI platform
• Contribute to Improve model tracking and monitoring
• Support Data engineers and data scientists by creating and managing big data clusters, environments for data exploration and visualization.
• A modern microservice architecture based on Java/Scala. We use a wide stack of technologies, of which, some of the most important are: Kubernetes, Docker, Ansible, Apache Cassandra, Scyladb, MySQL, Kafka, Elasticsearch, Redis, Memcache, Prometheus, Grafana, Debian Linux
• Building the necessary instrumentation, tooling, and alarming systems in order to escalate abnormalities.

What we offer

• International team - 30+ nationalities working together!
• Competitive salary
• Medical insurance
• Learning & sharing environment
• Flexible working hours
• Exciting company parties & team activities – Running team, Geek lunch!
• Start the day with fresh fruit and cereals
• Stay refreshed: get juice, tea, coffee, and soft drinks