Back to SearchLead Systems Engineer - Data DevOps/MLOps
Office in India: Chennai, & 5 others
Data DevOps& 19 others
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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.
Responsibilities
- 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
Requirements
- Bachelor's or Master's 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
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 demonstrating expertise in cloud platforms or data engineering tools