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Microsoft Machine Learning Engineer II 
United States 
852866610

30.07.2024

Required Qualifications:

  • Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering , or related field AND 2+ years experience in business analytics, data science, software development, data modeling or data engineering work
    • o OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering or related field AND 1+ year(s) experience in business analytics, data science, software development, or data engineering work
    • o OR equivalent experience.


Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check:
- This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.


Preferred Qualifications:

  • Bachelor's Degree in Computer Science , Math, Software Engineering, Computer Engineering , or related field AND 5+ years experience in business analytics, data science, software development, data modeling or data engineering work
    • o OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering , or related field AND 3+ years of business analytics, data science, software development, data modeling or data engineering work experience
    • o OR equivalent experience.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until August 5, 2024.

Responsibilities

• Design, develop, and maintain the data platform that power cybersecurity protection in our products and services.

• Collaborate with others to identify opportunities to optimize data tools used to transform, manage, and access data across teams. Ensures the effectiveness and placement of performance monitoring protocols across multiple data pipelines.

• Build optimized code to extract raw data from identified upstream sources and aggregate using query languages, while assuring accuracy, validity, and reliability of the data across the pipeline.

• Evaluate, propose, and implement relevant tools, technologies, and strategies to improve our end-to-end data, BI, and ML workflows.

• Defining and implementing measures and dashboards that accurately quantify the value of improvements.

  • Embody our