Hindustan Unilever Limited Hiring For 2023
Responsibilities of the Candidate:
- Collaborate with MLOps Sr Manager to transition models into the production environment after development and testing.
- Ensure that appropriate model maintenance guidelines and monitoring frameworks are in place during the handover of model ownership from the Data Science CoE to Solution Factory DevOps.
- Monitor and manage models in production, including retraining, monitoring model quality, data, and model drifting.
- Plan and manage model optimization and CI/CD automation tasks for the team.
- Govern incident management and routine MLOps activities.
- Provide regular overall quality reports to senior management.
- Manage Data Science solution DevOps requests with the Engagement Team for maintenance/minor enhancements.
- Coordinate and work with Data Science CoE to deliver significant model maintenance/enhancement work.
Requirements:
- End-to-end knowledge of advanced analytics models and lifecycle management.
- Knowledge of Azure Machine Learning, Databricks, experiment tracking, MLFlow, and integration between MLFLow and Azure Machine Learning Services.
- Knowledge of common data science algorithms and libraries (Spark MLlib, Scikit Learn).
- Strong code lifecycle management and CI/CD knowledge, especially in GitHub and Azure DevOps.
- Strong operation and service management skills.
- Wide experience in project and team management.
- Machine Learning qualification.
- Knowledge of container technology, especially Docker, ACS, Kubernetes.
- Python and PySpark coding experience.
- Deep learning tools and techniques.
- Strong Design Thinking/Agility and innovation mindset.
- Personal drive and ability to inspire and engage others.
- Credible business acumen with an understanding of business, commercials, and performance metrics.
- Encourages experimentation and intelligent risk-taking.
- Brings the voice of the consumer and internal customer into everything they do.
- Passion for high performance, creating motivation, and focus to drive execution at speed.
- Talent catalyst, encouraging collaboration and inclusivity, empowering teams to be their best.
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