Senior Systems Engineer

• Build CI/CD pipelines to support data integration and ML model deployment

• Set up and manage cloud-based infrastructure for data processing and model training

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

• Partner with data scientists, software engineers, and product teams to bring ML models into production

• Boost reliability and performance through optimized model serving and monitoring

• Maintain data versioning, lineage tracking, and reproducibility throughout ML experiments

• Pinpoint opportunities to strengthen deployment workflows, scalability, and infrastructure resilience

• Apply security protocols to protect data integrity and uphold compliance standards

• Troubleshoot and resolve issues throughout the data and ML pipeline lifecycle

Requirements

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

• At least 5 years of experience working in Data DevOps, MLOps, or similar roles

• Hands-on experience with cloud platforms including Azure, AWS, or GCP

• Working knowledge of Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Ansible

• Strong command of containerization and orchestration solutions like Docker and Kubernetes

• Experience working with data processing frameworks such as Apache Spark or Databricks

• Solid Python skills, along with familiarity with ML and data libraries like Pandas, TensorFlow, or PyTorch

• Exposure to CI/CD tools such as Jenkins, GitLab CI/CD, or GitHub Actions

• Familiarity with Git and MLOps platforms including MLflow or Kubeflow

• Experience with monitoring, logging, and alerting tools like Prometheus or Grafana

• Strong analytical and problem-solving skills, with the ability to work solo or as part of a team

  • Clear communication skills paired with strong documentation habits