DevOps Engineer / Senior Systems Engineer

We are looking for a detail-oriented and motivated Senior Systems Engineer with a strong focus on Data DevOps/MLOps to join our team. The ideal candidate should possess a deep understanding of data engineering, automation of data pipelines, and integration of machine learning models into operational environments. This role is for a collaborative professional adept at building, deploying, and managing scalable data and ML pipelines aligned with strategic objectives.

Design CI/CD pipelines for data integration and machine learning model deployment
Deploy and maintain infrastructure for data processing and model training using cloud services
Automate processes like data validation, transformation, and workflow orchestration
Coordinate with data scientists, software engineers, and product teams to integrate ML models into production environments
Enhance performance and reliability by optimizing model serving and monitoring processes
Ensure data versioning, lineage tracking, and reproducibility across ML experiments
Identify improvements for deployment processes, scalability, and infrastructure resilience
Implement security measures to safeguard data integrity and maintain compliance
Resolve issues in the data and ML pipeline lifecycle

Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field

• 4 or more years of experience in Data DevOps, MLOps, or related professions
• Proficiency in cloud platforms such as Azure, AWS, or GCP
• Expertise in containerization and orchestration tools such as Docker and Kubernetes
• Skills in using data processing frameworks like Apache Spark or Databricks
• Proficiency in Python, with familiarity with data manipulation and ML libraries such as Pandas, TensorFlow, or PyTorch
• Understanding of data governance frameworks and tools like Collibra

Knowledge of Big Data technologies such as Hadoop or Hive
Credentials in cloud platforms or data engineering activities