Back to SearchLead Systems Engineer - Data DevOps/MLOps
Office in India: Coimbatore, & 5 others
Data DevOps& 19 others
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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