Microsoft Looking For Machine Learning Engineer at Charlotte, NC Full Time

Are you someone with a passion for data, analytics, insights, and technology? Do you want to work on one of the largest data science teams at Microsoft, lighting up actionable insights that drive key business decisions for the Microsoft Cloud?

Team and Role:
The goal of the Microsoft Cloud Data Sciences (MCDS) team is to foster a data-driven culture; to encourage and enable the entire organization to make more informed decisions through data. In support of this mission, our team works closely with engineering, marketing, finance, and business leaders to identify opportunities for improving the customer experience and accelerating the growth of our business. Our charter spans the breadth of Cloud + AI, where we design and deliver standardized views of business performance, identify salient trends, define benchmarks and models for predicting upcoming performance, innovate with experimentations, and surface key insights. You can read more about our team’s work on Medium at (https://medium.com/data-scienceat-microsoft).

We are looking for an experienced Data Scientist to leverage data to unlock new value for Microsoft customers by understanding user behavior and service usage, create compelling offers, and optimize the customer experience across Microsoft Azure and Microsoft Cloud Products. The role primarily focused on building scalable and comprehensive experimentation analysis and statistical modeling solutions to discover the causal inference effects.

Responsibilities

KEY ACCOUNTABILITIES:
We are looking for strong system/data/MLOps engineers who can be expected to learn ML/Data Science concepts on the job.

You will leverage Azure services (e.g., Azure pipeline, Azure DevOps, Azure Data Factory) and develop customized modules to instrument the CI/CD capability.

You will support and manage machine learning models, production pipeline, experimentation platform across Data Science teams within and outside MCDS.

Develop and enhance reproducible, scalable analytical and modeling toolkits to provide rigorous analysis solutions. Convert ML scientist code into production-ready packages integrated into services and/or build applications.

Become a subject matter expert in the Cloud + AI business and underlying data ecosystem.

Lead the development and management of metrics, KPIs, and dashboards as needed.

Ensure the ongoing documentation of analysis methodologies and results.

The candidate will work closely with Applied Research Scientists, Data Engineers, Program Managers to design and implement a mature MLOPS platform.

I would suggest that me move this point under key accountabilities, as it is not really a qualification. [FL1]

Qualifications

BASIC QUALIFICATIONS

5+ years of strong systems and software engineering background as well as familiarity with various aspects of ML system design & management – this includes data engineering to design & monitor data pipelines that feed into ML model training and inferencing workflows, MLOPs best practices to permit continuous integration/continuous deployment (CI/CD) of newer artefacts in the ML production cycle, and management of ML models in production including continuous performance monitoring, incident resolution, and model retraining.

5+ years of experience with at least one of the cloud platforms, including Azure (Preferred), AWS, GDP, and have developed data pipeline related services.

5+ years of experience with database systems, including Relational Databases (e.g. SQL), and Graph Databases (e.g, Neo4j, Cosmos DB), and data storage systems, including Data Warehouse and Data Lake.

PREFERRED QUALIFICATIONS

Experience with one or more software programming languages including C, C++, C#, Scala, and Python

Excellent interpersonal, analytical, communication, and presentation skills – the ability to communicate complex findings in a simple manner.

Machine learning model development for production scenarios.

Familiarity with salient Machine Learning and Statistics concepts – confidence intervals, model performance validation, ML model training, basic probability theory and linear algebra

Advanced degree in Data Science, Machine Learning, Computer Science, Statistics, Applied Mathematics, or a related field.

Knowing Python is a plus.

PERSONAL ATTRIBUTES/INTERPERSONAL SKILLS:
Excellent written and oral communication skills, particularly the ability to synthesize complex problems/scenarios into easy-to-understand concepts.

Effective in rapidly evolving environments and working across organizational boundaries.

Organized thinker with high attention to detail.

A great teammate who seeks out collaboration opportunities, upholds a safe working environment, and values inclusivity in the workplace.

Creative, innovative, organized thinker, with a high attention to detail. #MCDSJOBS

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. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. 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.