Senior Machine Learning Ops Engineer

📋 Description

• Own architecture, development, and automation of end-to-end ML solutions.
• Bridge data science and software engineering across SDLC.
• Evaluate cloud solutions; deploy scalable ML models to production.

🎯 Requirements

• Bachelor’s degree in software engineering/computer science or proven equivalent in data engineering
• Hands-on experience deploying ML solutions in production.
• Core stack: Python, SQL, Spark.
• Tooling: Docker, Git, Bash Scripting, FastAPI, SageMaker Studio, Airflow, CloudFormation.
• Architecture & Integration: strong data architectures and systems integration.
• Cloud Platforms: AWS and GCP experience.

🎁 Benefits

• Long-term contract with high impact and autonomy.
• Strategic, high-visibility role in modern engineering culture.
• Opportunity to influence tech strategy, esp. MLOps, data architectures, and cloud cost-efficiency.
• Collaborative international team with strong technical leadership.
• Flexible, dynamic, fast-paced environment.