Applied Scientist II

Posted 3 Days Ago
Mountain View, CA, USA
In-Office
102K-219K Annually
Junior
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Design and train large-scale text and numeric models for ad response prediction, own end-to-end model training and data pipelines, develop evaluation and A/B experimentation frameworks, and deliver production-grade ML systems that improve marketplace and advertiser outcomes.
Summary Generated by Built In
Overview

Our team (Signals Modeling) builds the core intelligence that understands and predicts how users interact with ads - from the first impression through clicks, post-click engagement, and downstream business outcomes. 

We design and train text and numerical models with billions of parameters that power ad ranking across large-scale consumer surfaces. The team owns end-to-end ML systems, including large-scale data and label construction, representation learning, multi-task and proxy objectives, calibration, and rigorous offline and online evaluation. We build sophisticated training pipelines that transform weak signals (e.g., page visits, dwell time, or engagement events) into high-quality learning targets.

Engineers and scientists on the team work at the intersection of deep learning, large-scale experimentation, and marketplace economics, shipping production-grade models and data pipelines that directly drive revenue and advertiser ROI. This is a hands-on builder role where you will see your models make measurable impact in one of the world’s largest ads ecosystems.

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.  

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.


Responsibilities
  • Drive modeling and data innovations for user response modeling for advertising.
  • Develop rigorous evaluation and experimentation frameworks to assess impact of model improvements on the marketplace.
  • Own model training and data pipelines end-to-end, ensuring the reliability and overall health of the modeling stack.

Qualifications

Required Qualifications:

  • Bachelor's Degree in 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 Computer Science, Electrical or Computer Engineering, or related field
    • OR equivalent experience.

Preferred Qualifications:

  • Master's Degree in Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
    • OR Doctorate in Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • Experience with large-scale online marketplaces or ads/recommendation systems.
  • Proven technical ability in cross-team modeling efforts or platform-level ML systems.
  • 2+ years of industry experience building and shipping machine learning models in production.
  • Proven experience with modern ML models (e.g., deep learning, tree-based models, or linear models) and feature engineering.
  • Understanding of supervised learning and multi-task learning.
  • Practical experience working with large-scale, real-world data and building end-to-end modeling pipelines (data preparation, training, validation, deployment).
  • Experience with offline evaluation and online A/B experimentation for ML systems.
  • Proven programming skills in Python and at least one major ML framework (e.g., PyTorch or TensorFlow).
  • Ability to independently drive modeling projects from problem definition through production and iteration.

#MicrosoftAI 


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 Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience
  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience
  • Doctorate in Computer Science, Electrical or Computer Engineering, or related field
  • Equivalent experience (in lieu of degree)
  • Master's Degree in Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
  • Doctorate in Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience
  • Experience with large-scale online marketplaces or ads/recommendation systems
  • Proven technical ability in cross-team modeling efforts or platform-level ML systems
  • 2+ years of industry experience building and shipping machine learning models in production
  • Proven experience with modern ML models (deep learning, tree-based models, or linear models) and feature engineering
  • Practical experience building end-to-end modeling pipelines (data preparation, training, validation, deployment)
  • Experience with offline evaluation and online A/B experimentation for ML systems
  • Programming skills in Python and at least one major ML framework (e.g., PyTorch or TensorFlow)
  • Ability to independently drive modeling projects from problem definition through production and iteration

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.

  • Fair & Transparent Compensation Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
  • Retirement Support Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
  • Parental & Family Support Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.

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

What We Do

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