Azure Machine Learning Engineer ID 2732
Azure Machine Learning Engineer ID 2732
Posted on :
10-02-2025
Employer Active
1 Vacancy
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Jobs by Experience
10years
Salary
Not Disclosed
Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
10-02-2025
Job Description
As an Azure Machine Learning Engineer you will:
- Design develop and deploy machine learning models in Azure focusing on Batch Prediction and Endpoint Deployment.
- Ensure endtoend ML model lifecycle management from data ingestion and model training to deployment and monitoring.
- Implement best practices for MLOps including automation CI/CD pipelines and scalability.
- Work closely with data scientists and software engineers to translate business needs into productionready ML solutions.
- Optimize ML models for performance costefficiency and scalability in cloud environments.
- Troubleshoot and resolve issues in production ML systems ensuring high availability and reliability.
What You Bring to the Table:
- 10 years of experience in Machine Learning Engineering Software Engineering or Data Science.
- Strong expertise in Azure Machine Learning particularly in Batch Prediction and Endpoint Deployment.
- Deep understanding of ML model deployment monitoring and optimization in Azure.
- Proficiency in MLOps CI/CD pipelines and cloudnative ML workflows.
- Handson experience with Python SQL and ML frameworks (TensorFlow PyTorch or Scikitlearn).
- Strong problemsolving skills with the ability to optimize and troubleshoot ML systems in production.
You should possess the ability to:
- Work independently and collaboratively in highly technical ML engineering environments.
- Bridge the gap between data science and software engineering to deploy scalable ML solutions.
- Leverage Azure cloud services for ML model deployment and optimization.
- Ensure security compliance and performance standards for ML applications in production.
- Continuously improve and refine ML workflows to meet business and operational needs.
What We Bring to the Table:
- Opportunity to work with cuttingedge ML technologies in Azure.
- A dynamic and collaborative environment that fosters innovation and technical excellence.
- Competitive compensation and benefits tailored to industry standards.
- Career growth opportunities in AI/ML engineering and cloudbased machine learning.
As an Azure Machine Learning Engineer, you will: Design, develop, and deploy machine learning models in Azure, focusing on Batch Prediction and Endpoint Deployment. Ensure end-to-end ML model lifecycle management, from data ingestion and model training to deployment and monitoring. Implement best practices for MLOps, including automation, CI/CD pipelines, and scalability. Work closely with data scientists and software engineers to translate business needs into production-ready ML solutions. Optimize ML models for performance, cost-efficiency, and scalability in cloud environments. Troubleshoot and resolve issues in production ML systems, ensuring high availability and reliability. What You Bring to the Table: 10+ years of experience in Machine Learning Engineering, Software Engineering, or Data Science. Strong expertise in Azure Machine Learning, particularly in Batch Prediction and Endpoint Deployment. Deep understanding of ML model deployment, monitoring, and optimization in Azure. Proficiency in MLOps, CI/CD pipelines, and cloud-native ML workflows. Hands-on experience with Python, SQL, and ML frameworks (TensorFlow, PyTorch, or Scikit-learn). Strong problem-solving skills with the ability to optimize and troubleshoot ML systems in production. You should possess the ability to: Work independently and collaboratively in highly technical ML engineering environments. Bridge the gap between data science and software engineering to deploy scalable ML solutions. Leverage Azure cloud services for ML model deployment and optimization. Ensure security, compliance, and performance standards for ML applications in production. Continuously improve and refine ML workflows to meet business and operational needs. What We Bring to the Table: Opportunity to work with cutting-edge ML technologies in Azure. A dynamic and collaborative environment that fosters innovation and technical excellence. Competitive compensation and benefits tailored to industry standards. Career growth opportunities in AI/ML engineering and cloud-based machine learning.
Employment Type
Full Time
Key Skills
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