EY - GDS Consulting - AI And DATA - ML Ops Specialist - Manager

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Job Title: Senior ML Ops Specialist - Manager

Experience: 8-12 years

Job Summary: 

We are seeking an experienced Senior ML Ops Specialist to join our team, focusing on delivering robust machine learning operations in the banking and insurance sectors. The ideal candidate will have extensive experience in ML Ops and AI Ops, with a strong background in deploying and managing machine learning models in production environments, particularly using Azure. This role will involve leading the implementation of best practices for ML operations and ensuring the reliability and scalability of AI solutions.

Key Responsibilities:

• Lead the design, implementation, and management of ML Ops pipelines to streamline the deployment, monitoring, and maintenance of machine learning models in production.
• Collaborate with data scientists, engineers, and business stakeholders to ensure seamless integration of ML models into existing systems and workflows.
• Utilize Azure services for deploying, managing, and scaling machine learning applications and infrastructure effectively.
• Monitor model performance, implement strategies for continuous improvement, and optimize model efficiency and reliability.
• Develop and maintain comprehensive documentation for ML Ops processes, workflows, and best practices.
• Implement AI Ops practices to enhance operational efficiency and reliability of AI systems across banking and insurance applications.
• Troubleshoot and resolve complex issues related to model deployment, performance, and data quality.
• Stay updated on industry trends and advancements in ML Ops and AI Ops, providing strategic recommendations for implementation.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
• 8-12 years of experience in ML Ops and AI Ops, preferably in the banking and insurance sectors.
• Proficiency in programming languages such as Python or R, with extensive experience in ML frameworks (e.g., TensorFlow, PyTorch).
• Strong understanding of Azure services related to machine learning (e.g., Azure Machine Learning, Azure DevOps).
• Proven experience with CI/CD practices for machine learning model deployment and automation.
• Excellent analytical and problem-solving skills, with a focus on delivering reliable and scalable AI solutions.
• Strong leadership and communication skills, with the ability to work effectively in a collaborative environment.

Preferred Skills:

• Familiarity with containerization technologies (e.g., Docker, Kubernetes) for deploying ML models.
• Knowledge of data governance and compliance standards in the banking and insurance sectors.
• Experience with monitoring and logging tools for AI systems.

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