MLOps Engineer

Description :

Key Responsibilities :

- Develop and maintain scalable and reliable infrastructure for hosting and serving machine learning models in the cloud.

- Monitor model performance in production, identify and troubleshoot issues, and implement solutions to maintain accuracy and stability.

- Collaborate with data scientists to optimize model performance and ensure seamless integration with existing systems.

- Automate data ingestion, transformation, and feature engineering processes to streamline model development and deployment.

- Implement robust data governance and security measures to protect sensitive data and ensure compliance with industry regulations.

- Contribute to the development of best practices for ML-Ops and promote a culture of continuous improvement.

Required Skillset :

- Proven experience in deploying and managing machine learning models in cloud environments such as AWS, Azure, or GCP.

- Strong understanding of Linux operating systems and scripting languages such as Python or Bash.

- Expertise in data management and data engineering principles, including data warehousing, ETL processes, and data quality.

- Ability to effectively communicate technical concepts to both technical and non-technical audiences.

- Experience with containerization technologies such as Docker and orchestration tools like Kubernetes.

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- 1-3 years of relevant experience in an ML-Ops or related role.

- Ability to work effectively in a fast-paced, collaborative environment.