Description:

Collaborate with Data Science teams to implement Machine Learning models into production.
Design and deliver GenAI solutions and manage industrialized processing pipelines.
Implement best practices in ML models life cycle and MLOps/LLMOps frameworks.
Present solutions and create technical documentation.

Requirements:

5+ years of Data engineering experience, with 3 years in building Data processing.
5+ years of production-ready Python code development experience.
3+ years of experience in production-ready ML-related code development.
1+ year of experience with GenAI technologies (e.g., ChatGPT, Gemini).
Practical experience with MLOps tools like AzureML/AzureAI and Databricks.
Good understanding of ML/AI concepts and Cloud architectures (preferably Azure or GCP).
Experience in data domains such as Data Warehouse, Data Lake, and MLOps.
Strong communication skills and ability to work in a team.

Skills

Benefits