Data & Applied Scientist II

At Microsoft, we understand the importance of breaking down language barriers to better serve our global customers. Our Customer Success Engineering team is fully committed to this mission, and our team, "Magic," plays a critical role in modernizing localization and internationalization platforms. Our goal is to empower partners to build products for international markets and enable Microsoft to move faster in delighting billions of customers worldwide.

The “Magic” team at Microsoft is seeking a motivated and talented Data & Applied Scientist II to join our team and help build the next generation localization pipeline, including cutting-edge machine translation systems and language quality prediction and estimation models using innovative Deep Learning and AI technologies, including OpenAI’s GPT models.

This position offers an outstanding and unique opportunity to be part of a team that impacts and empowers Microsoft customers around the globe with delightful and world-class user experience, while maintaining a diverse, agile, and supportive team environment.

As part of the team, you will be building end-to-end ML/AI powered features through their entire life cycle from idea creation through implementation, experimentation and finally to worldwide availability in partnership with our engineering teams.

The right candidate will have a strong passion for deep learning, language technology and passion for delighting users through building quality international experiences.

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.

Responsibilities

• Investigate, design, prototype, test, validate and deliver scalable machine learning solutions that help us maintain and improve localization quality while increasing velocity using best in class technologies and frameworks, applying the latest approaches from AI/ML research.
• Collaborate with multiple disciplines: Product Managers, UX Designers, Data Scientists, Software Engineers, and partner teams to deliver and contribute to production-ready solutions.
• Leverage Azure services (e.g., Azure ML, Azure DevOps, Azure Data Factory) and develop customized modules to instrument the MLOps practice.
• Support and manage machine learning models, the production pipeline, and experimentation platform, contributing to all stages of prompt engineering, model fine-tuning, deployment and monitoring.
  
  

Qualifications

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 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 related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
• OR equivalent experience.
• Software development experience, including hands-on demonstrable experience in developing Machine Learning/Deep Learning solutions, in particular their use in Natural Language Processing (NLP) solutions.
• Expertise in various ML frameworks and libraries (Scikit-learn, PyTorch/TensorFlow, Azure ML, OpenAI).
  

Other Requirements

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.
  
  

Preferred Qualifications

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 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 related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical.
• Experience creating publications (e.g., patents, peer-reviewed academic papers) in the fields of ML, data science, predictive analytis or AI.
• Fluency with recent NLP & ML advancements e.g. large language models, as well as a driven passion for discovering the next generation of technology.
• Experience working on Machine Translation or language-related tasks would offer a distinct advantage.
• Excellent knowledge of experimental design and evaluation.
• Experience working in a technical problem domain (plan, design, execution, continuous release, and service operation) and bringing cutting-edge research ideas into production.
• Proven track record of shipping Machine Learning models.
• Excellent communication skills, inter-personal & collaboration skills.
• Proficiency with data engineering and working with large data sets (structured and unstructured), relational databases, database-design and ELT.
  

#CSE

Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.