Microsoft Member Technical Staff AI - Pre-Training 

United States, Washington 

147169946

and product deployment.some of the mostin deep learning at scale.will deliver one of the best

• Have provenexpertisein areas of interest,evidencedby an exceptional publicationtrack record

• experience and/or in-depth understandings about large-scale distributed systems

• Demonstrate an ability to work collaboratively in a fast-paced, innovative environment

Required Qualifications

• Bachelor's Degree in Computer Science,Machine Learning, Mathematics,or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.

Preferred Qualifications

• Bachelor's Degree in Computer Scienceor related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • ORMaster's Degree in Computer Scienceor related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.
• Demonstrated experience in large-scale AI.
• Passionate about conversational AI and its deployment.
• Demonstrated written and verbal communication skills with the ability to work closely with cross-functional teams, including product managers, designers, and other engineers.
• Passion for learningnew technologiesand staying up to date with industry trends, best practices, and emerging technologies in AI.
• Proven ability to collaborate and contribute to a positive, inclusive work environment, fostering knowledge sharing and growth within the team.

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

• algorithms, model architectures, data mixtures, and scaling laws for large-scale training using a rigorous data-driven approach grounded in meticulous ablations

• algorithmic implementations, conductexperiments, and overseeflagship training runs on our in-house large-scale distributed stack

• Embody ourand