Microsoft 365 is at the core of Microsoft mission to enable people and organizations to achieve more. Intelligent Data Engineering and Analytics (IDEAs) services handle millions of users and exabytes of data. This is not just some large-scale web service: the implementation ranks among the world’s largest and state of the art distributed systems, spanning across data centers around the world.

Microsoft 365 IDEAs team’s goal is to help customers improve productivity,  champion a data-informed culture, and enable the entire Microsoft 365 organization to make more informed decisions through data. We see this effort as a huge opportunity in providing information to both external and internal users that will improve efficiency, empowerment, and helps Microsoft win in the critical cloud business sector.

Responsibilities

• Work closely with Data Scientists, Program Managers, and Platform Engineers to design and implement high-quality end-to-end ML solutions in production (including data ingestion, feature engineering, training, scoring, monitoring, telemetry, and endpoint integration) 
• Research innovative ways to optimize all aspects of managing models in production to reduce implementation times and ensure best possible model quality and performance (including algorithms, parameter tuning, compute environments, model management tools, feature selection) 

• Onboard feature data from a wide variety of sources and manage a high-quality feature store to support production models and data scientist productivity 
• Build a deep understanding of Microsoft ML platforms and open-source frameworks to guide what capabilities we can adopt in our environment 
• Develop packages and tools to streamline the model onboarding and management 
• Monitor production model performance and health, identify where improvements need to be made, and handle production incidents when they occur  

Qualifications

Required Qualifications 

• Bachelor’s degree in Computer Science, Machine Learning, Data Science 
• 1+ years experience implementing and optimizing a variety of ML algorithms in production (Regression, Deep Learning, Gradient Boosting, Dimensionality Reduction) 
• Solid Python programming skills and coding practices (CI/CD, package design, unit testing, etc) 
• Solid experience with common machine learning frameworks: TensorFlow, PyTorch, Keras, Spark ML 
• Experience joining and processing terabyte data sources into curated feature datasets (batch and streaming methods) 

• Experience implementing API interfaces for model serving (i.e. OpenAPI, FastAI) 

Desired Qualifications 

• Experience on optimizing models on various types of compute (CPU/GPU, Spark, Kubernetes) 
• Experience with orchestration frameworks like Azure Data Factory, AirFlow or equivalent 
• Knowledge of statistics and experiment design (i.e. A/B testing, causal inference) 
• Experience with containerization: Docker, Kubernetes 
• Experience with Azure Machine Learning (or equivalent) 
• Experience with ML Ops frameworks like MLFlow, KubeFlow or equivalent  
• Experience with compiled languages:  C++, C#, or Java 
• Experience with Microsoft analytic systems: Cosmos, Kusto, Substrate AI, Synapse 

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.