Senior Systems Engineer - Data DevOps/MLOps

Job Description

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 4+ 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