About the role
KEY ACCOUNTABILITIES
- Design, develop, and maintain end-to-end MLOps pipelines using GCP, Vertex AI, Airflow, Kubeflow, and MLflow.
- Build and optimize data ingestion, transformation, deployment, monitoring, retraining, and CI/CD/CT pipelines for production ML solutions.
- Implement MLOps best practices, including version control, coding standards, workflow orchestration, and lifecycle management.
- Design scalable ML solution architectures and recommend technology stacks aligned with business and technical requirements.
- Provide production support, troubleshoot issues, perform root cause analysis, and drive continuous platform improvements.
- Mentor team members through code reviews, technical guidance, and knowledge-sharing on MLOps frameworks and best practices.
- Collaborate with Data Science, Data Engineering, Platform, and Business teams to deliver scalable ML solutions.
- Research, document, and adopt emerging MLOps technologies, architecture patterns, and engineering best practices to drive innovation.
MINIMUM QUALIFICATIONS
Education: Minimum qualification is Bachelor's degree (full time)
Experience: Minimum 6+ yrs of professional experience in MLOps E2E framework and 10+ years of total experience
Technical Skills: Expertise in Data Transformation and Manipulation through Big-Query/SQL, Professional experience with Vertex AI and GCP Services, Expertise in one of the programming Language Python/R, Should have experience in Airflow/Cloud composer, Kubernetes/Kubeflow, MLflow, TFX,Docker -container
Soft Skills: Strong communication skills both verbal and written including the ability to interact effectively with colleagues of varying technical and non-technical. Passionate about agile software processes, data-driven development, reliability, and systematic
PREFERRED QUALIFICATIONS
- GCP certification
- Understanding of CPG industry
- Basic understanding of DBT, AutoML Concept
ELIGIBILITY
Applicants must meet minimum age qualifications in the country in which the job is located.
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