Data Engineering Specialist – Data Architecture

📋 Description

• Create and sustain MLOps pipelines to facilitate the automation of the machine learning model lifecycle.

• Develop and enhance CI/CD pipelines tailored to machine learning workflows.

• Regularly assess model performance in production, focusing on logs, metrics, and alerts.

• Formulate and implement strategies to identify and address any performance decline in models.

• Guarantee the security, governance, and compliance of data and models in production settings.

• Work collaboratively with cross-functional teams to document and standardize MLOps-related processes.

⛳️ Requirements

• Extensive experience in MLOps, including the automation and integration of pipelines.

• Proficient with containerization technologies (Docker, Kubernetes) and workflow orchestration, as well as familiarity with cloud providers (AWS) and their machine learning services. Competence in Python for data operations and model workflows.

• Background in implementing monitoring, logging, and observability for production models. Strong knowledge of data security, governance, and compliance best practices.

🏝️ Benefits

• Freedom to work from anywhere

• Flexible working hours

• Education assistance

• Proprietary career development tool

• Internal guilds and study/interest groups

• Health insurance

• Dental insurance

• Discounted medication purchase partnership

• 24/7 telemedicine

• Free online therapy

• Wellhub

• Extended maternity leave

• Extended paternity leave

• CAZ – Zuppers Support Center

• Meal and grocery vouchers

• Life insurance

• Transport allowance

• Home office allowance

• Childcare allowance

• Phone plan allowance

• Profit-sharing (Participation in Profits and Results)