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Lead Systems Engineer - Data DevOps/MLOps

Hybrid in Chennai
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Data DevOps
& others
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We are seeking a skilled and passionate Lead Systems Engineer with Data DevOps/MLOps expertise to drive innovation and efficiency across our data and machine learning operations.

Responsibilities
  • Design, deploy, and manage CI/CD pipelines for seamless data integration and ML model deployment
  • Establish robust infrastructure for processing, training, and serving machine learning models using cloud-based solutions
  • Automate critical workflows such as data validation, transformation, and orchestration for streamlined operations
  • Collaborate with cross-functional teams, including data scientists and engineers, to integrate ML solutions into production environments
  • Improve model serving, performance monitoring, and reliability in production ecosystems
  • Ensure data versioning, lineage tracking, and reproducibility across ML experiments and workflows
  • Identify and implement opportunities to improve scalability, efficiency, and resilience of the infrastructure
  • Enforce rigorous security measures to safeguard data and ensure compliance with relevant regulations
  • Debug and resolve technical issues in data pipelines and ML deployment workflows
Requirements
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
  • 8+ years of experience in Data DevOps, MLOps, or related disciplines
  • Expertise in cloud platforms such as Azure, AWS, or GCP
  • Skills in Infrastructure as Code tools like Terraform, CloudFormation, or Ansible
  • Proficiency in containerization and orchestration technologies such as Docker and Kubernetes
  • Hands-on experience with data processing frameworks including Apache Spark and Databricks
  • Proficiency in Python with familiarity with libraries including Pandas, TensorFlow, and PyTorch
  • Knowledge of CI/CD tools such as Jenkins, GitLab CI/CD, and GitHub Actions
  • Experience with version control systems and MLOps platforms including Git, MLflow, and Kubeflow
  • Understanding of monitoring and alerting tools like Prometheus and Grafana
  • Strong problem-solving and independent decision-making capabilities
  • Effective communication and technical documentation skills
Nice to have
  • Background in DataOps methodologies and tools such as Airflow or dbt
  • Knowledge of data governance platforms like Collibra
  • Familiarity with Big Data technologies such as Hadoop or Hive
  • Showcase of certifications in cloud platforms or data engineering tools