backGo to search

Senior Systems Engineer - Data DevOps/MLOps

Hybrid in Hyderabad, Bangalore, Pune, Gurgaon
bullets
Data DevOps
& others
bullets
hot

We are looking for a skilled and motivated Senior Systems Engineer with expertise in Data DevOps/MLOps to join our team.

The ideal candidate must possess a strong understanding of data engineering, automation for data pipelines, and operationalizing machine learning models. This role requires a collaborative professional capable of building, deploying, and managing scalable data and ML pipelines that meet business objectives.

Responsibilities
  • Design, deploy, and manage CI/CD pipelines for data integration and machine learning model deployment
  • Build and maintain infrastructure for data processing and model training using cloud-native tools and services
  • Automate processes for data validation, transformation, and workflow orchestration
  • Coordinate with data scientists, software engineers, and product teams to enable seamless integration of ML models into production
  • Optimize performance and reliability of model serving and monitoring solutions
  • Manage data versioning, lineage tracking, and reproducibility for ML experiments
  • Identify opportunities to enhance scalability, streamline deployment processes, and improve infrastructure resilience
  • Implement security measures to safeguard data integrity and ensure regulatory compliance
  • Diagnose and resolve issues throughout the data and ML pipeline lifecycle
Requirements
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
  • 4+ years of experience in Data DevOps, MLOps, or similar roles
  • Proficiency in cloud platforms like Azure, AWS, or GCP
  • Competency in using Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Ansible
  • Expertise in containerization and orchestration technologies like Docker and Kubernetes
  • Background in data processing frameworks such as Apache Spark or Databricks
  • Skills in Python programming, with proficiency in data manipulation and ML libraries like Pandas, TensorFlow, and PyTorch
  • Familiarity with CI/CD tools, including Jenkins, GitLab CI/CD, or GitHub Actions
  • Understanding of version control tools like Git and MLOps platforms such as MLflow or Kubeflow
  • Knowledge of monitoring, logging, and alerting systems (e.g., Prometheus, Grafana)
  • Strong problem-solving skills and ability to contribute both independently and within a team
  • Excellent communication skills and attention to documentation
Nice to have
  • Knowledge of DataOps practices and tools like Airflow or dbt
  • Understanding of data governance concepts and platforms such as Collibra
  • Background in Big Data technologies like Hadoop or Hive
  • Qualifications in cloud platforms or data engineering