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Associate Principal
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Full Stack Data Scientist
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Lead MLOps Engineer
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MLOps Engineer
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Backend Engineer
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Data Scientist
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Senior Data Scientist
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MLOps Engineer
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MLOps Azure Engineer
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Senior Machine Learning Operations Engineer
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Senior Machine Learning Operations Engineer
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Data Science Intern
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ML Ops/DevOps Engineer
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Senior Software Engineer
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Machine Learning Architect
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MLOps Engineer
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MLOps Developer - Any Location, India - GOOGNU DATA SERVICES PRIVATE LIMITED
![Default job background](https://contents.bebee.com/public/img/bg-user-ex-1.jpg)
Description
Position: Senior MLOps Engineer
Company: Tech Innovations Inc.
- Design and Implement MLOps Infrastructure: Building and maintaining robust MLOps workflows using Azure Machine Learning and other Azure services to automate the machine learning lifecycle from data preparation to model deployment and monitoring.
Collaboration with Cross-Functional Teams: Working closely with data scientists, software developers, and IT specialists to ensure the seamless integration and deployment of ML models into production.
Continuous Monitoring and Optimization: Monitoring the performance of machine learning models in production, identifying issues with model drift, and optimizing them for performance and scalability.
Data Governance and Security: Implementing and enforcing data governance and security policies compliant with industry standards, ensuring data integrity and privacy.
Research and Development: Keeping up to date with the latest developments in MLOps technologies and Azure services. Evaluating and adopting new tools and practices to enhance the deployment process and model performance.
Mentorship and Leadership: Providing guidance and mentorship to junior MLOps engineers and team members, fostering a culture of learning and continuous improvement.
Education: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
Professional Experience: Minimum of 6 years of experience in a role focusing on machine learning, data engineering, or software development, with at least 3 years dedicated to MLOps.
Technical Skills:
- Proficiency in Azure Machine Learning, Azure Data Factory, Azure Databricks, and other relevant Azure services.
Strong experience in automating and orchestrating ML workflows at scale.
Knowledge of Python, SQL, and other scripting languages commonly used in data processing.
Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.
Experience with CI/CD tools and practices in a machine learning context.