Lead Systems Engineer - Data DevOps/MLOps

We're looking for a talented and dedicated Lead Systems Engineer who brings Data DevOps/MLOps expertise to enhance innovation and streamline our data and machine learning operations.
Responsibilities
Build, launch, and oversee CI/CD pipelines that enable smooth data integration and ML model deployment
Set up a reliable infrastructure to process, train, and serve machine learning models through cloud platforms
Streamline essential workflows including data validation, transformation, and orchestration through automation
Partner with cross-functional teams such as data scientists and engineers to bring ML solutions into live production environments
Enhance model serving capabilities, performance tracking, and dependability within production systems
Maintain data versioning, lineage tracking, and reproducibility throughout ML experiments and workflows
Spot and act on opportunities to boost scalability, efficiency, and resilience across infrastructure
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
Requirements
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related discipline
At least 8 years of experience working in Data DevOps, MLOps, or similar fields
Strong command of cloud platforms including Azure, AWS, or GCP
Proficiency with Infrastructure as Code tools such as Terraform, CloudFormation, or Ansible
Solid grasp of containerization and orchestration tools 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 working with version control systems and MLOps platforms like Git, MLflow, and Kubeflow
Working knowledge of monitoring and alerting tools such as Prometheus and Grafana
Solid problem-solving skills paired with the ability to make independent decisions
Clear communication abilities and strong technical documentation skills
Nice to have
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 related to cloud platforms or data engineering tools

Work arrangement
No