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The Signals Team at Microsoft Ads develops advanced machine learning models to predict user responses to advertisements. These predictive signals play a crucial role in enhancing user engagement and maximizing advertiser returns. As a Principal Applied Scientist on our team, you will design and implement large-scale machine learning models, driving their deployment into production and translating your expertise into tangible revenue impact. This role offers a unique opportunity to enhance your skills in building and deploying machine learning models at scale. You will gain invaluable experience analyzing model behavior within a complex, multi-layered model stack, and understanding the intricate interactions between various algorithms. Additionally, you will stay at the forefront of state-of-the-art approaches in this domain.
Job Responsibility:
Build large scale machine learning models for text and numerical data, deploy models in production
Run A/B testing, analyze impact of model metrics and possible model failure modes on business KPIs
Conduct data exploration and analysis of new features and model improvements
Establish scalable pipelines for data processing and analytics, model training and validation
Establish automated processes to monitor system health using agentic workflows
Track relevant state-of-the-art approaches in the field, identify and implement applications to improve the modeling stack
Mentor less experienced scientists on the team
Requirements:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ 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 4+ years related experience
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
Nice to have:
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience
OR equivalent experience
5+ years customer-facing, project-delivery experience, professional services, and/or consulting experience
Machine Learning Model Expertise: Deep experience designing, training, and optimizing large-scale machine learning models, particularly transformer-based models and large language models, with a strong focus on production deployment and performance
LLM Inference & Fine-Tuning: Proven ability to build and optimize high-performance LLM inference pipelines and apply advanced fine-tuning techniques (e.g., SFT, LoRA, RLHF) to adapt foundation models for domain-specific use cases
Model Quality & Evaluation: Strong expertise in developing robust evaluation frameworks for ML and LLM systems, including automated metrics, human evaluation, benchmarking, and monitoring for issues such as hallucination, bias, safety, and model regression