Senior Systems Engineer

• Build, launch, and oversee CI/CD pipelines supporting data integration and ML model rollout

• Establish and maintain cloud-based infrastructure for data processing and model training

• Streamline data validation, transformation, and workflow orchestration through automation

• Partner with data scientists, software engineers, and product teams to ensure seamless ML model integration into production environments

• Improve model serving and monitoring capabilities to increase performance and reliability

• Oversee data versioning, lineage tracking, and reproducibility of ML experiments

• Continuously identify opportunities to improve deployment workflows, scalability, and infrastructure resilience

• Enforce robust security measures to protect data integrity and ensure regulatory compliance

• Diagnose and resolve problems across the entire data and ML pipeline lifecycle

Requirements

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related discipline

• Minimum 5 years of experience in Data DevOps, MLOps, or comparable positions

• Skilled in cloud platforms such as Azure, AWS, or GCP

• Experienced with Infrastructure as Code tools like Terraform, CloudFormation, or Ansible

• Strong knowledge of containerization and orchestration tools, including Docker and Kubernetes

• Practical experience with data processing frameworks such as Apache Spark and Databricks

• Skilled in programming languages like Python, with familiarity in data manipulation and ML libraries such as Pandas, TensorFlow, and PyTorch

• Knowledgeable in CI/CD tools such as Jenkins, GitLab CI/CD, and GitHub Actions

• Experienced with version control systems and MLOps platforms including Git, MLflow, and Kubeflow

• Solid grasp of monitoring, logging, and alerting tools such as Prometheus and Grafana

• Strong problem-solving skills with the ability to perform well both independently and collaboratively

  • Excellent communication and documentation abilities