ML Ops Specialist
ML Ops Specialist
Posted on :
10-07-2025
Employer Active
1 Vacancy
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Job Description
Key Responsibilities and nbsp;
ML Ops Strategy and amp; Implementation: Design implement and maintain end-to-end MLOps pipelines ensuring seamless integration of machine learning models into production environments. and nbsp;
Model Deployment and amp; Monitoring: Utilize Azure ML services to deploy models efficiently and monitor their performance ensuring reliability and scalability. and nbsp;
CI/CD Pipeline Development: Develop and manage continuous integration and continuous deployment pipelines using Azure DevOps or similar tools to automate model training testing and deployment processes.
Collaboration and amp; Consultation: Work closely with data scientists engineers and business stakeholders to understand requirements and translate them into robust MLOps solutions. and nbsp;
Performance Optimization: Implement strategies for model optimization including hyperparameter tuning and resource management to enhance model accuracy and efficiency. and nbsp;
Governance and amp; Compliance: Ensure that deployed models adhere to organizational policies security standards and regulatory requirements. and nbsp;
Required Skills and amp; Qualifications and nbsp;
Experience: Minimum of 5 years in machine learning roles with at least 23 years focused on MLOps specifically in deploying and managing models in production. and nbsp;
Technical Proficiency: and nbsp;
Strong programming skills in Python including frameworks like Flask FastAPI and libraries such as Pandas and NumPy. and nbsp;
Hands-on experience with Azure Machine Learning including model training deployment and monitoring. and nbsp;
Familiarity with containerization technologies like Docker and orchestration tools such as Kubernetes. and nbsp;
Experience with CI/CD tools like Azure DevOps GitLab CI or GitHub Actions. and nbsp;
Knowledge of MLflow Azure Databricks and Azure Kubernetes Service (AKS). and nbsp;
Portfolio: Demonstrated experience with at least 23 production-level implementations of machine learning models showcasing the ability to transition models from development to production environments effectively. and nbsp;
Soft Skills: Excellent communication and consulting skills with the ability to collaborate across teams and present complex technical concepts to non-technical stakeholders. and nbsp;
Preferred Qualifications and nbsp;
Experience with model governance drift detection and performance monitoring in production settings. and nbsp;
Familiarity with Azure governance tools cost management and policy enforcement. and nbsp;
Exposure to Agile methodologies and project management tools like Azure Boards or JIRA. and nbsp;
and nbsp;
Employment Type
Full Time
Key Skills
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