MLOps Engineer

Role:

Required Experience:

Job Location:

Must Have Skills:

Key Responsibilities:

• Collaborating with data scientists to understand model requirements, gather data, and refine models.
• Responsible for the lifecycle of models, once deployed in production environments, through monitoring performance and model evolution.
• Solve technical problems related to data processing, model building, and deployment.
• Building and training machine learning models, including selecting datasets, performing statistical analysis, and refining models.
• Deploy machine learning models to production environments, ensuring that models are integrated with software systems.
• Monitor machine learning models in production, ensuring that models are performing as expected and that any errors or performance issues are identified and resolved quickly.

Required Skills:

• Strong background in Data Science with hands-on ML experience and MLOps
• Proficiency in Python and related libraries (Pandas, NumPy, Scikit-learn, etc.).
• Ability to handle large-scale data and build end-to-end ML pipelines.
• Hands on experience with MLflow, Kubeflow, Airflow, Docker, Kubernetes, SageMaker, Azure ML, Vertex AI.
• Good understanding of statistical methods and data analysis.