Job Summary:
A Machine Learning Operations (MLOps) Specialist plays a vital role in bridging the gap between data science and IT operations ensuring seamless integration of machine learning models into production environments. Heres a breakdown of the job:
Key Responsibilities:
Developing and Maintaining CI/CD Pipelines: Create automated workflows for building testing and deploying machine learning models.
Automating Deployment and Monitoring: Ensure models are deployed efficiently and their performance is continuously tracked in production environments.
Implementing Infrastructure as Code (IaC): Manage ML infrastructure using code to ensure consistency and scalability.
Troubleshooting and Resolving Issues: Identify and fix problems related to model deployment and performance.
Collaboration: Work with data scientists and engineers to optimize model performance scalability and integration.
Requirements:
Education: Bachelors degree in Computer Science Engineering or a related field.
Experience: 5 years in MLOps DevOps or a related role.
Technical Expertise: Strong understanding of machine learning concepts algorithms and cloud platforms (AWS Azure GCP).
Scripting Skills: Proficiency in Python or similar scripting languages.
Containerization: Experience with Docker and Kubernetes.
CI/CD Tools: Familiarity with Jenkins GitLab CI CircleCI or similar.
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