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Phoenix Financial Linkedin · Posted 6d ago

MLOps Engineer

Rishon LeZion

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Indexed description

About The Phoenix Group:

The Phoenix Group is a leading financial institution driving innovation through data and AI. We are looking for an experienced MLOps Engineer to join our Data, AI, and Machine Learning teams and help shape our next-generation AI infrastructure.


Position Overview:

We are looking for an experienced MLOps Engineer to join our Data, AI, and Machine Learning teams. This role combines software engineering, cloud infrastructure, automation, and a deep understanding of the machine learning lifecycle. The position involves designing, building, developing, and continuously improving the infrastructure required for training, deploying, and maintaining Machine Learning models in production environments, while working closely with Data Science, Data Engineering, Development, Architecture, DevOps, Information Security, and business stakeholders.


Key Responsibilities:

• Design, build, and maintain end-to-end ML and ETL pipelines, including model training, validation, and deployment processes.

• Develop and maintain CI/CD pipelines and implement AWS services and infrastructure.

• Build and enhance ML infrastructure with a strong focus on production environments and monitoring capabilities.

• Design and develop architectures for LLM-based products and solutions.

• Implement DevOps methodologies, develop automation processes, and create and maintain infrastructure blueprints.


Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related field.

• At least 2 years of experience in a similar role working with ML systems in production environments.

• Proven experience building and operating ML pipelines on AWS.

• Hands-on experience with Docker, Git, and CI/CD processes.

• Strong proficiency in Python and experience developing and maintaining production-grade ML code.

• Proven experience working in Linux environments.

• Knowledge of networking and communication protocols – a significant advantage.

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