Related skills
bigquery docker sql python apache airflow📋 Description
- Design, build, and maintain ML infrastructure powering models and AI agents.
- Enable other engineering teams to ship AI features into production.
- Collaborate with Data Scientists to improve model accuracy, reliability, and scalability.
- Lead end-to-end MLOps practices and share knowledge with the team.
- Deploy, monitor, and optimize ML models on GCP (VertexAI, GKE).
- Shape the Data R&D delivery from research to product implementation.
🎯 Requirements
- Extensive MLOps experience deploying ML models including Generative AI at scale.
- Strong hands-on experience with Google Cloud Platform: BigQuery, VertexAI, GKE.
- Proficient in Python and SQL.
- Experience building data pipelines with Apache Airflow.
- Familiar with ML frameworks like TensorFlow, PyTorch, scikit-learn.
- Knowledge of CI/CD pipelines (GitLab CI) and model monitoring.
🎁 Benefits
- Flexible time off to manage work-life balance.
- Career development through workshops, frameworks, and trainings.
- Impactful work shaping products used by 85,000+ users worldwide.
- Mobility options: mobility budget or company car.
- Net allowance: support for home office-related expenses.
- Vouchers: Lunch vouchers and Eco vouchers.
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