▸ Participate in the entire development lifecycle of the MLOps platform
▸ Collaborate with Front-end developers to integrate user-facing elements with server side logic
▸ Collaborate with data engineers and data scientists to assist in the practical implementation of complex domain knowledgecould accelerate the ML dev cycle (MLOPs).
▸ Ability to adapt flexibly to various unforeseen and unfamiliar challenges
▸ Build reusable code and libraries for future use

▋What Skill/Experience You Must Have:
▸ Proficient in Python and Experience Python web frameworks (We use Django & Django Rest Framework)
▸ In-depth understanding containerized technologies and management tools (e.g Docker, Kubernetes, Helm)
▸ Experience in parallel task processing.
▸ Familiar with RDBMS (We use PostgreSQL) and having experience of performance tuning
▸ Familiar with cloud platforms (e.g. Azure, AWS, GCP)
▸ Familiar with writing unit tests, integrations tests and automation
▸ Experience in CI/CD tools (e.g. Github Action, Jenkins and Drone CI)

▋Add-On Value

- Experience in designing the architecture of Elastic Stack components
- Knowledge of infrastructure-as-code concepts and experience in tools (e.g. Terraform, Ansible, etc.)
- Knowledge of monitoring and log analysis tools (e.g. Grafana, Prometheus, Loki, etc.)
- Experience in developing SaaS products
- Strong understanding of Computer Science / Engineering fundamentals and first principles covering system design, data structures, architecture, and design patterns
- Experience in Deep learning / Computer Vision / Image Process / Face Recognition related tools (e.g. TensorFlow, PyTorch, OpenCV or dlib, etc.)
- Big Data Experience (e.g. Airflow, Hadoop, Kafka, Apache Spark, Cassandra, etc.)
- Aware of all sorts of agile ceremonies ****(e.g. user story grooming, sprint planning, sprint retrospective)