Microsoft Senior Applied Scientist Microsoft AI 

United States, Washington 

444900595

Some examples of our work include:

• Building the LLM based Deep Search that even more relevant and comprehensive answers to the most complex search queries.
• Developing a massive sparse neural network to improve search relevance (covered by SiliconAngle, Search Engine Land, Venture Beat)
• Building the world’s most comprehensive spelling correction system through zero shot learning (covered by NextWeb, Venture Beat, and ZDNet)
• Using transformer networks for search (covered in Search Engine Land and in State of AI 2020 report)
• Launching our technology as a cloud service on Azure (a summary of the technologies we used)
• Delivering on innovative page summarization experiences (covered on Search Engine Land and onMSFT)
• Open sourcing our vector search algorithm (covered by Ars Technica and TechCrunch)
• Building and open sourcing blazing fast transformer network inferencing (covered in ZDNet and Forbes) Deep learning based question answering and captions (covered in VentureBeat, Search Engine Land)
• including developing our own accelerated chips for inferencing
• Co-developing our large scale training library called DeepSpeed (covered in SiliconAngle, The Batch)

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
• 4+ years of industry experience applying Machine Learning techniques.
• Experience with machine learning frameworks such as TensorFlow or PyTorch.

Preferred Qualifications:

• Experience building large scale cloud-based solutions.
  
• Customer focused, strategic, drives for results, is self-motivated, and has a propensity for action.

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

• Advance the state-of-the-art machine learning and NLP algorithms for real-world large-scale search and recommendation systems and applications.
• Work on the full lifecycle of machine learning development including training data collection, feature engineering, model training, offline and online experimentation, and deployment.
• Mentor and grow engineers in the team.