Applied Sciences IC3
Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Artificial Intelligence
In short
Our Signals Modeling team at Microsoft AI is seeking an Applied Sciences IC3 to build core intelligence for understanding and predicting user interaction with ads. This role involves designing and training large-scale text and numerical models, owning end-to-end ML systems, and driving innovations in user response modeling and evaluation frameworks. The position requires strong programming skills in Python and ML frameworks, with a focus on shipping production-grade models that impact the ads ecosystem.
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.
Requirements
- 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.
Desired 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.
Benefits
- 4 days / week in-office
- Less than 25% travel
- Typical base pay range for this role across the U.S. is USD $102,100 - $202,200 per year.
- In San Francisco Bay area and New York City metropolitan area, the base pay range is USD $133,800 - $219,200 per year.
- Certain roles may be eligible for benefits and other compensation.
#Machine Learning#Data Science#Advertising#Research#Applied Sciences#Signals Modeling#Deep Learning#Experimentation#Marketplace Economics#Production Models#Data Pipelines#User Response Modeling#Evaluation Frameworks#ML Systems#Feature Engineering#Supervised Learning#Multi-task Learning#Offline Evaluation#Online A/B Experimentation#Python#PyTorch#TensorFlow
Company
Microsoft
Job Posted
1 month ago
Employment Type
Full Time
WorkMode
On Site
Experience Level
Mid-Senior
Locations
United States
Qualification
Bachelor, Master, Doctoral
Applicants
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