Machine Learning Engineer

Job description:

For our client we're currently looking for a senior machine learning engineer.
**job description:**
**GCP requirements:**
- Familiar with Vertex AI pipeline/kubeflow pipelines
- Familiar with BigQuery,
- can code SQL
- Familiar with Cloud composer / airflow
- Familiar with IAM, service account
- Familiar with Data catalog
- Understand Infrastructure as Code
- Good to have knowledge with Dataflow, and K8s.
**Cloud agnostic skills:**
- Python:
- Deep knowledge about python programing, practice OOP, following coding best practice, know how to use flake8, mypy, black, SonarQube and pre-commit
- Deep knowledge in unit test and end to end test, familiar with Pytest, fixtures, unittest etc
- DBT
- Deep Knowledge in DBT, preferably with GCP
- Unix:
- Familiar with popular Unix system, know how to install sth in docker.
- Familiar with shell
- Git:
- Know how to create PR and solve merge conflict.
- Can create CI/CD pipeline in either Github Action using best practice
- Docker
- Deep understanding with Docker
- SQL
- Deep knowledge of SQL
- Deep understanding with Data modeling, system design
**Soft skills:**
- Can do attitude,
- Problem solving, even if there is sth new that you don't know. You have a proper way to solve it. For example, knowing how to Google is always good.
- Communication skills with Stakeholders and tech ppl.
- Love code review and feedback
This role is in a team that works with customer-facing recommendation systems, so previous experience with high-availability APIs, machine learning–based recommendations, and personalization systems is considered a merit.