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Machine Learning Workflow Engineer
3 weeks ago
Job Description
The MLOps Engineer is responsible for streamlining machine learning project lifecycles by designing and automating workflows. They collaborate with stakeholders to set up infrastructure, automate model deployment, monitor models, and scale training.
Key Responsibilities:
- Designing and automating machine learning workflows
- Collaborating with stakeholders to set up infrastructure
- Automating model deployment and monitoring
- Scaling training processes
Requirements:
- Proficiency in Python and scripting languages like Bash or PowerShell
- Knowledge of orchestration and scheduling tools like Airflow, Prefect, Dagster, etc.
- Understanding of ML algorithms and distributed training
- Experience with GCP and BigQuery DWH platform
- Hands-on experience with Kubeflow and Vertex AI
- Familiarity with tools like MLFlow from the operations perspective
- Experience with containerization technologies like Docker and knowledge of container orchestration platforms like Kubernetes
- Understanding of continuous integration and continuous deployment (CI/CD) practices
Benefits
- Sport subscription
- Private healthcare
- Flat structure
- Small teams
- International projects
- Team Events
- Training budget
- Free coffee
- Gym
- Bike parking
- Playroom
- Free snacks
- Free beverages
- In-house trainings
