Senior Systems Engineer - Data DevOps/MLOps

We are looking for a skilled and motivated Senior Systems Engineer with expertise in Data DevOps/MLOps to join our team.

The ideal candidate must possess a strong understanding of data engineering, automation for data pipelines, and operationalizing machine learning models. This role requires a collaborative professional capable of building, deploying, and managing scalable data and ML pipelines that meet business objectives.

Responsibilities

• Design, deploy, and manage CI/CD pipelines for data integration and machine learning model deployment
• Build and maintain infrastructure for data processing and model training using cloud-native tools and services
• Automate processes for data validation, transformation, and workflow orchestration
• Coordinate with data scientists, software engineers, and product teams to enable seamless integration of ML models into production
• Optimize performance and reliability of model serving and monitoring solutions
• Manage data versioning, lineage tracking, and reproducibility for ML experiments
• Identify opportunities to enhance scalability, streamline deployment processes, and improve infrastructure resilience
• Implement security measures to safeguard data integrity and ensure regulatory compliance
• Diagnose and resolve issues throughout the data and ML pipeline lifecycle

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
• 5+ years of experience in Data DevOps, MLOps, or similar roles
• Proficiency in cloud platforms like Azure, AWS, or GCP
• Competency in using Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Ansible
• Expertise in containerization and orchestration technologies like Docker and Kubernetes
• Background in data processing frameworks such as Apache Spark or Databricks
• Skills in Python programming, with proficiency in data manipulation and ML libraries like Pandas, TensorFlow, and PyTorch
• Familiarity with CI/CD tools, including Jenkins, GitLab CI/CD, or GitHub Actions
• Understanding of version control tools like Git and MLOps platforms such as MLflow or Kubeflow
• Knowledge of monitoring, logging, and alerting systems (e.g., Prometheus, Grafana)
• Strong problem-solving skills and ability to contribute both independently and within a team
• Excellent communication skills and attention to documentation

Nice to have

• Knowledge of DataOps practices and tools like Airflow or dbt
• Understanding of data governance concepts and platforms such as Collibra
• Background in Big Data technologies like Hadoop or Hive
• Qualifications in cloud platforms or data engineering