Microsoft Machine Learning Engineer (MLE) Interview Guide

As the creator of the Microsoft 365 productivity suite and Windows operating system, Microsoft is rightfully one of the most recognizable technology brands in the world. In recent years, it’s focused on AI and machine learning through software products like its cloud platform, Azure, which powers many AI innovators like OpenAI.

If you’re passionate about developing and enhancing AI systems that impact millions, a machine learning engineer (MLE) role at Microsoft could be a great fit for you. In this guide, we explain how machine learning engineers contribute to Microsoft’s mission and how to prepare for its MLE interview process.

What does a Microsoft MLE do?

Machine learning at Microsoft takes form in a variety of ways, which reflects the size of the company and its breadth of projects. For example, Microsoft’s cloud computing platform Azure depends on AI infrastructure and ML models. However, ML and AI go far beyond Azure and are woven throughout the company in cloud-based solutions, customer service, user security, and more.

Microsoft’s MLE roles are attached to specific teams and projects. Unlike other tech companies that conduct teams-matching rounds alongside a hiring offer, Microsoft looks for candidates to fill a specific role.

The day-to-day of an MLE depends on which team you apply for. For example, an MLE on the Industry Solutions team works side-by-side with customer engineers to create seamless digital experiences for Microsoft’s diverse user base, while Azure MLEs collaborate with their team to build the responsible AI infrastructure and prompt flow used by developers worldwide.

In terms of compensation, Microsoft MLE salaries generally range from $175,000 to $245,000 per year, including bonus and stock.

What are the typical job requirements for a Microsoft MLE?

Education: For most MLE roles, Microsoft seeks a bachelor's degree with a set number of years of experience (generally 4+ years minimum). A master’s degree is preferred, but seldom required.

Likewise, your major is less important than your technical experience. While a computer science degree (or related field) makes you a stronger candidate, a history of successfully displaying your ML skill set is ultimately more important.

Experience: Microsoft’s MLE roles generally require 4-6+ years of experience, with 8-10+ years preferred for senior roles.

Since every role has unique requirements, we’ve included a few examples for various MLE positions below.

Here are the requirements for an MLE working on the Industry Solutions team:

Required:

• B.S. in computer science (or related field)
• 6+ years in engineering
• Ability to code in languages including but not limited to: C, C++, C#, Java, JavaScript, and/or Python

Preferred:

• M.Sc. in computer science (or related field)
• 8-10+ years in technical engineering
• Confidence in communicating complex AI concepts and solutions to both technical and non-technical audiences
• Experience with cloud services, preferably Azure

Here are the requirements for a senior MLE working on the Human-centered AI Experiences team:

Required:

• B.S. in computer science (or related field)
• 4+ years in technical engineering
• Ability to code in languages including but not limited to: C, C++, C#, Java, and/or JavaScript
• 3+ years coding in Python
• 1+ years using ML frameworks such as PyTorch, Tensorflow, and scikit learn
• 3+ years managing resources in a cloud platform, and running distributed machine learning experiments

Preferred:

• M.Sc. in computer science (or related field)
• 6-8+ years in technical engineering
• Experience training and evaluating machine learning models for NLP, Vision, and Multimodal tasks
• Experience in development for research projects that fall into one of the following research areas: reliability and robustness of AI systems, rigorous evaluation and benchmarking, advances in AI interpretability, bias and fairness, and safety in real-world deployments

Recommendations before you apply for Microsoft MLE roles

• Look into Microsoft’s recent projects. A strong working knowledge of Microsoft products, as well as its mission and vision, can set you apart in a pool of applicants. Brushing up on Microsoft’s ML/AI ventures and being able to quickly and efficiently describe how Microsoft products interact with one another shows interest in the brand.
• Develop a clear and compelling pitch. Microsoft recruiters hear from hundreds of candidates every day, so it’s essential to find a way to stand out. Prepare both written and verbal elevator pitches of varying lengths (30 seconds, 2 minutes, and 5 minutes are good benchmarks) that you can share with recruiters. Remember to be friendly and polite in your communication.
• Prepare anecdotes about your experience working on a team. Although Microsoft MLEs are individual contributors, they frequently collaborate with other engineers and stakeholders. Think about times when you’ve worked on a team, and be prepared to articulate what you bring to a collaborative environment.

Interview Process

Microsoft’s MLE interview loop is relatively standardized and features:

• A recruiter screen with a mix of behavioral and technical questions
• An ML fundamentals interview to assess your understanding of ML/AI concepts
• A technical principles and methods interview for general coding/hands-on problem-solving
• A meeting with a hiring manager and/or team manager to discuss your overall fit as a potential team member

All Microsoft interviews are virtual and take place on Microsoft Teams unless another software is needed.

Below, we go through each interview stage in more detail.

Recruiter Screening

The first stage of the Microsoft MLE interview process is a short recruiter call (roughly 30 minutes) to see if you are a good fit for the company. Expect a mix of standard behavioral questions, alongside preliminary technical tests.

Prepare to explain why you would be a good culture fit at Microsoft, and express interest and knowledge in their product ecosystem whenever possible. From here, your recruiter will share additional insights on how the next interviews are structured.

Popular behavioral questions at Microsoft include:

Machine Learning Fundamentals

The interviews after your recruiter screen are more technical. The ML fundamentals interview is all about your ability to understand, articulate, and solve complex ML and AI problems.

In these interviews, Microsoft is looking for:

• Confidence articulating ML and coding concepts
• Familiarity with Microsoft’s current use of AI in its product ecosystems
• Ability to discuss previous technical engineering work

If your prospective role requires knowledge of ML frameworks (PyTorch, Tensorflow, scikit learn, etc), make sure that you are ready to display your particular skill set in that framework.

Here are some Microsoft machine learning questions you can expect:

• How do you evaluate an ML model?
• What is a confusion matrix?
• What are some common transformations for categorical data?
• Explain when accuracy would be a good metric and a bad metric to measure how well your model is performing.

Past candidates report that in this interview, they were asked about their experience with Azure and cloud computing. Make sure you have familiarity (and preferably a strong competency) with the Azure ecosystem before interviewing with Microsoft.

Technical Principles and Methods

Coding is essential to any MLE role at Microsoft. This technical interview is centered around your ability to problem-solve quickly and efficiently to help keep Microsoft products running smoothly. While the content of this interview may vary depending on your team, a dedication to building your technical skill set is essential.

In these interviews, Microsoft is looking for:

• Excellence in the coding language(s) listed on your job posting
• Speed and efficiency in your problem-solving
• Ability to explain your reasoning behind the choices you make

Here are some general coding questions you can expect:

Check out Exponent’s extensive Coding Interview Practice as a resource for improving your ability to solve coding questions and effectively articulate your process.

Hiring Manager Call

If you make it through the three behavioral/technical interviews, you’ll have a final interview with a hiring manager and/or your team leader. This interview focuses on your work location and hours, as well as additional onboarding information.

In recent years, Microsoft has fully embraced the flexible workplace. Many roles are hybrid or fully work-from-home, and others have “multiple locations” listed where team members can live while working the role. Microsoft recognizes that different people thrive on different schedules, and has built the opportunity to work the hours that are best for you into many of their jobs.

This conversation is less of an assessment, and more of an opportunity to discuss and customize your work experience at Microsoft. You may be asked a few final general behavioral questions, similar to those of the recruiter screen, but the core of this interview is figuring out the practical details of your next steps with Microsoft.

Tips and Strategies

As a massive company that’s interviewed and onboarded hundreds of thousands of candidates, Microsoft has shared many of its own hiring tips and what makes a candidate stand out.

Microsoft prides itself on a strong sense of culture and achievement, and encourages prospective hires to engage with the product ecosystems before applying to develop a passion for and literacy in Microsoft products. Additionally, Microsoft lists a set of core competencies that drive its product vision:

• Collaboration. Communicating effectively within the team and across teams.
• Drive for results. Working tenaciously to deliver on commitments, constantly seeking bigger challenges, holding yourself and others accountable.
• Customer focus. Our mission at Microsoft is to empower every person and every organization to achieve more.
• Influencing for impact. Successfully persuading and influencing others with effective communication.
• Judgment. Effectively scoping complex problems and using business acumen to make knowledge-based decisions.
• Adaptability. Ability to deal with ambiguous and uncertain situations or problems with agility.

Product vision is important, but Microsoft also seeks candidates who are driven by a desire to build a strong internal company culture. Below are its organizational values:

• Growth mindset. True learners who can acquire new skills rapidly and connect with others to help bring big ideas to life.
• Diverse and inclusive. Being open to learning about your own biases and changing behaviors accordingly. Value differences, seek them out, and invite them in.
• One Microsoft. Actively seeks collaboration with others and looks for common ground across differences, contributes to and builds on success of others, and prioritizes for customer and team within their role.
• Customer obsession. The ability to learn about customers' perspectives, show empathy to their experiences, and incorporate these insights into their decisions and deliverables.
• Values. When we come together, we treat each other with respect, we act with integrity, and we are accountable to one another for our words and actions.
• Manager expectations. Our managers help bring our culture to life. As they model, coach, and care, they help reinforce our culture and create an environment where everyone can do their best work.

Additional Resources

• Microsoft Careers Site
• Azure Machine Learning
• Machine Learning Engineer Interview Course
• Software Engineering Interview Course
• Top Microsoft Machine Learning Engineer Interview Questions
• Top Microsoft Interview Questions
• Top Data Structures & Algorithms Questions

FAQs

• Are Microsoft interviews in person or virtual? All Microsoft interviews are virtual and held on Microsoft Teams. If Teams doesn’t have the capabilities needed for a technical interview, it may be held on a third-party platform.
• Can I interview again if I’m rejected? Yes, Microsoft encourages candidates to reapply a minimum of 6 months after their rejection if they see a different position that is a good potential fit for them.
• What is Microsoft’s mission statement? Microsoft’s global mission is "to empower every person and every organization on the planet to achieve more." Learn more about the company’s vision, culture, and stories.
• Does Microsoft offer internships? Yes! Microsoft has a highly competitive internship/recent graduate program. While it offers data science internships, most are research-oriented. Hands-on ML engineering jobs tend to be reserved for full-time team members since they are highly complex and essential to the success of Microsoft products.