Lead Systems Engineer Data DevOpsMLOps

We are looking for a talented and dedicated Lead Systems Engineer who brings Data DevOps/MLOps experience to enhance innovation and efficiency throughout our data and machine learning operations.

• Build launch and oversee CI/CD pipelines that enable smooth data integration and ML model deployment
• Build dependable infrastructure to support processing training and serving of machine learning models through cloud-based platforms
• Streamline key processes like data validation transformation and orchestration to enhance operational efficiency
• Partner with cross-functional teams such as data scientists and engineers to embed ML solutions within production systems
• Enhance model serving performance tracking and reliability within production environments
• Maintain data versioning lineage tracking and reproducibility throughout ML experiments and workflows
• Discover and apply strategies to boost the scalability efficiency and resilience of infrastructure systems
• Apply strict security protocols to protect data and maintain compliance with applicable regulations
• Troubleshoot and fix technical problems within data pipelines and ML deployment processes

• Bachelors or Masters degree in Computer Science Data Engineering or similar field
• 8 years of professional background in Data DevOps MLOps or comparable areas
• Strong command of cloud platforms including Azure AWS or GCP
• Capability with Infrastructure as Code tools such as Terraform CloudFormation or Ansible
• Competency in containerization and orchestration solutions like Docker and Kubernetes
• Practical experience using data processing frameworks such as Apache Spark and Databricks
• Strong Python skills along with familiarity with libraries like Pandas TensorFlow and PyTorch
• Familiarity with CI/CD tools including Jenkins GitLab CI/CD and GitHub Actions
• Background using version control systems and MLOps platforms such as Git MLflow and Kubeflow
• Working knowledge of monitoring and alerting tools like Prometheus and Grafana
• Solid problem-solving skills paired with the ability to make independent decisions
• Strong communication abilities and technical documentation expertise

• Experience with DataOps approaches and tools like Airflow or dbt
• Familiarity with data governance platforms such as Collibra
• Exposure to Big Data technologies including Hadoop or Hive
• Certifications demonstrating expertise in cloud platforms or data engineering tools