Senior Applied Scientist, Microsoft AI

1 Month ago • 3-7 Years • Artificial Intelligence • $117,200 PA - $250,200 PA

Job Summary

Job Description

The Senior Applied Scientist at Microsoft AI will advance state-of-the-art machine learning and NLP algorithms for large-scale search and recommendation systems. Responsibilities include the full machine learning lifecycle, from data collection and feature engineering to model training, experimentation, and deployment. The role requires working with massive datasets and building cutting-edge solutions for Bing and other search engines, leveraging technologies like LLMs and transformer networks. Mentoring team members is also a key aspect. The team focuses on innovative search technologies, including summarization, personalization, and question answering, impacting hundreds of millions of users.
Must have:
  • 4+ years applying ML techniques
  • Experience with TensorFlow or PyTorch
  • Building large-scale solutions
  • Bachelor's degree in related field
Good to have:
  • Experience building cloud-based solutions
  • Customer focus, strategic thinking
Perks:
  • Industry-leading healthcare
  • Educational resources
  • Product and service discounts
  • Savings and investment options
  • Maternity/paternity leave
  • Generous time away
  • Giving programs
  • Networking opportunities

Job Details

Overview

The Core Search and AI team is the leading applied machine learning team at Microsoft responsible for delivering the highest-quality search experience to over 500M+ monthly active users around the world in Microsoft’s search engine, Bing and other dependent search engines such as Yahoo, DuckDuckGo, and new startups like Neeva. We are looking for a Senior Applied Scientist, Microsoft AI to join us. 

 

We have seen little innovation in search in the last decade and we are looking for people who want to build the next generation of search using advanced AI technologies at scale. We are responsible for the largest machine learning models at Microsoft by volume and take pride in being the first in the world to solve many practical AI at Scale challenges. Our work spans a very large scope of scenarios including delivering high quality search results from a massive document corpus, extractive and abstractive summarization to generate document snippets, personalization, machine reading comprehension, and document recommendations.

As a team, we leverage the diverse backgrounds and experiences of passionate engineers, scientists, and program managers to help us realize our goal of making the world smarter and more productive. We believe great products are built by inclusive teams of customer-obsessed individuals who trust each other and work together closely.  We collaborate regularly across the company both to find the technology breakthroughs from groups like Microsoft Research to infusing AI into the rest of Microsoft products like Office and Azure.
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)

If you are passionate about working on the latest and hottest areas that will help you develop skills in Artificial Intelligence, Machine Learning, data science and high scale systems, this is the team you’re looking for! 

 

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Qualifications

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.

Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $153,600 - $250,200 per year.

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 4, 2025

 

Responsibilities

  • 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.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Opportunities to network and connect

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