Applied Scientist - AI Experiences Search

Reposted 10 Hours Ago
Redmond, WA, USA
In-Office
102K-219K Annually
Junior
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Conduct end-to-end applied research and engineering to improve web data quality, scalability, and readiness for Search, grounding, and LLM training. Develop machine learning, statistical, data mining, and LLM-based methods; analyze web-scale data; design experiments; apply prompt engineering for data evaluation and labeling; and translate research findings into product decisions and technical roadmaps. Collaborate across teams to establish scalable, responsible, privacy-conscious AI practices.
Summary Generated by Built In
Overview

The Microsoft AI Web Data team is seeking an Applied Scientist to help build the next-generation platform for Bing and Microsoft AI.


The Microsoft AIX Web Data Platform (WDP) team builds the data foundation that powers Bing and Microsoft AI experiences, including large-scale grounding and large language model (LLM) training. We operate end-to-end systems that discover, crawl, process, understand and store web content on the internet scale. We advance the platform’s capabilities with state-of-the-art modeling and fueling critical Microsoft experiences and pushing the frontier of AI.


This is a great opportunity for someone who enjoys tackling deep technical challenges and driving industry-wide impact. In this role, you will translate research into production by advancing the state of the art and applying it to meet today’s AI needs. You will drive the design, development, execution, and implementation of research projects, using scientific principles and techniques to develop, evaluate, and deploy algorithms and solutions that improve system performance, quality, data management, and accuracy.


Join us to shape the future of AI and deliver meaningful value to millions of users. 

 

At Microsoft, our mission—to empower every person and every organization on the planet to achieve more—guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress—people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone. 


Responsibilities
  • Own end-to-end applied research and engineering to improve web data quality, scale, and model readiness for Search, grounding, and LLM training.
  • Develop and apply state-of-the-art machine learning, LLM, statistical, and data mining techniques to solve complex web-scale problems and advance platform capabilities.
  • Analyze large-scale web data, formulate hypotheses, and design rigorous experiments that produce trustworthy, actionable insights and measurable impact.
  • Apply LLMs and prompt engineering to score, classify, label, and evaluate data, enabling scalable model training, evaluation, and continuous improvement.
  • Translate complex technical problems and research findings into product decisions, technical strategies, and engineering roadmap in partnership with stakeholders.
  • Collaborate across Microsoft AI, document and share learnings, and establish best practices for scalable, responsible, and privacy-conscious AI and data solutions.  

Qualifications

Required Qualifications:  

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
    • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
    • OR equivalent experience. 

Preferred Qualifications: 

  • 1+ years of experience contributing to research publications, patents, or peer-reviewed academic papers.
  • 1+ years of experience in product development in machine learning and related areas.
  • Hands-on experience developing algorithms and models using deep learning frameworks such as TensorFlow and PyTorchHands-on experience with large language models (LLMs), such as GPT, BERT, or similar architectures, with an understanding of their capabilities and limitations. 
  • Knowledge of natural language processing (NLP), including tokenization, semantic understanding, representation learning, classification, and text generation.
  • Understanding of modern machine learning and deep learning techniques, with hands-on experience using architectures such as Transformers/Attention, DNNs, CNNs, or RNNs and frameworks such as PyTorch, TensorFlow, or Keras.
  • Algorithmic, statistical, and analytical skills, with demonstrated ability to apply advanced techniques to complex, real-world problems.
  • Ability to translate technical vision into experimentation, system design, implementation, and measurable results, working both independently and collaboratively across teams.
  • Experience with large-scale or distributed data processing, high-performance computing, stream processing, or SCOPE is preferred.

Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 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 $133,800 - $219,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay


This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.



Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Skills Required

  • Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical Engineering, Computer Engineering, or a related field, plus 2 or more years of related experience
  • Master's degree in Statistics, Econometrics, Computer Science, Electrical Engineering, Computer Engineering, or a related field, plus 1 or more years of related experience
  • Doctorate in Statistics, Econometrics, Computer Science, Electrical Engineering, Computer Engineering, or a related field
  • Equivalent experience
  • At least 1 year contributing to research publications, patents, or peer-reviewed academic papers
  • At least 1 year of product development experience in machine learning or related areas
  • Hands-on experience developing algorithms and models with TensorFlow or PyTorch
  • Hands-on experience with large language models such as GPT or BERT
  • Knowledge of natural language processing, including tokenization, semantic understanding, representation learning, classification, and text generation
  • Understanding of modern machine learning and deep learning techniques, including Transformers, attention, DNNs, CNNs, or RNNs
  • Algorithmic, statistical, and analytical skills applied to complex real-world problems
  • Ability to translate technical vision into experimentation, system design, implementation, and measurable results
  • Experience with large-scale or distributed data processing, high-performance computing, stream processing, or SCOPE

Microsoft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.

  • Healthcare Strength — Health coverage is described as comprehensive, with preventive care coverage, vision options, and annual out-of-pocket limits. Feedback suggests medical, mental-health, and disability support are a major strength of the package.
  • Parental & Family Support — Family support is expansive, including parental leave, family caregiver leave, child-care assistance, family concierge services, fertility options, and college-advising support for eligible employees. Feedback suggests these benefits meaningfully ease caregiving and family planning demands.
  • Wellbeing & Lifestyle Benefits — Wellbeing resources include counseling and employee-assistance services, wellness reimbursements, product discounts, and charitable-matching programs. Feedback suggests these extras complement core benefits and support day-to-day quality of life.

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The Company
HQ: Redmond, WA
206,870 Employees
Year Founded: 1975

What We Do

At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. Our mission is grounded in both the world in which we live and the future we strive to create. Today, we live in a mobile-first, cloud-first world, and the transformation we are driving across our businesses is designed to enable Microsoft and our customers to thrive in this world.

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