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Microsoft Machine Learning Engineer II 
United States, Washington 
646419118

24.12.2024

Required Qualifications:

  • Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

o OR equivalent experience.

  • 2+ years experience in machine learning, deep learning and/or related fields.
  • 2+ year experience in software development experience in languages such as Python, Java, C++, Scala, or C#
  • 2+ year experience developing end to end ML (Machine Learning)/DL (Deep Learning) engineering systems.
  • 2+ year experience in distributed/cloud computing systems (e.g. Spark, Hadoop, Azure, AWS, Cosmos).

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 Cloud Background Check upon hire/transfer and every two years thereafter.


Preferred Qualifications:

  • Have research or work experience on NLP, or recommendation system.
  • Experience working in the Gen AI field.
  • Experience developing and designing science model consumed in production development.
  • Experience working through full product cycles from initial design to final product delivery.
  • Knowledge and experience in large scale data analytics, such as Spark.

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 January 6, 2025.

Responsibilities

We are seeking an enthusiastic AI engineer who is passionate about the latest AI advancements, possesses a start-up mindset, and is willing to take on any challenge.

  1. Coding to model optimization
  2. Model quantization
  3. Participate in design, implementation, and execution across a variety feature including building ML/DL models.
  4. Analyze complex, high-volume, high-dimensionality data.
  5. Participate in designing and building Responsible AI harmful content model core.
  6. Collaborate with a team of world-class researchers, scientists & engineers to solve very challenging problems.

Other:

  • Embody our and