Carnegie Mellon University’s Software Engineering Institute (SEI) is a leader in applied artificial intelligence research and engineering, focusing on developing innovative technologies for defense and national security.

As a Research Scientist within the SEI AI Division, you will engage in hands-on research in applied machine learning and artificial intelligence, addressing critical needs within the U.S. government. This role emphasizes collaboration with interdisciplinary teams to develop operational capabilities, influence national research agendas, and mentor team members, all while focusing on the practical design and implementation of AI technologies. Ideal candidates possess a deep technical knowledge in machine learning, strong communication skills, and a dedication to innovation and creativity. Your work will contribute to building secure, robust, and human-centered AI systems that address real-world challenges.

This guide will equip you with the insights and knowledge needed to excel in your interview, helping you to articulate your expertise and alignment with the values and mission of the SEI.

The interview process for the Research Scientist role at the Software Engineering Institute (SEI) is structured to assess both technical expertise and collaborative skills essential for conducting advanced research in applied artificial intelligence and machine learning. Here’s what you can expect:

1. Initial Screening

The process begins with an initial screening, typically conducted via a phone call with a recruiter. This conversation will focus on your background, experience, and motivation for applying to the SEI. The recruiter will also provide insights into the organization's culture and the specific expectations for the Research Scientist role.

2. Technical Interview

Following the initial screening, candidates will participate in a technical interview, which may be conducted via video conferencing. This interview will assess your knowledge and experience in machine learning, artificial intelligence, and relevant programming languages such as Python. Expect to discuss your previous research projects, methodologies, and any hands-on experience you have with algorithms and data analysis.

3. Research Presentation

Candidates who advance to this stage will be asked to prepare a presentation on a relevant research topic. This is an opportunity to showcase your expertise, communication skills, and ability to convey complex ideas clearly. The presentation will be followed by a Q&A session where interviewers will probe deeper into your research approach and findings.

4. Behavioral Interview

The behavioral interview focuses on assessing your soft skills, including teamwork, collaboration, and problem-solving abilities. Interviewers will explore your experiences working in interdisciplinary teams, mentoring others, and how you handle challenges in a research environment. Be prepared to provide specific examples that demonstrate your ability to work effectively with diverse stakeholders.

5. Final Interview

The final interview typically involves meeting with senior leadership or key stakeholders within the SEI. This round will delve into your alignment with the organization's mission and values, as well as your vision for contributing to the research agenda. Expect discussions around strategic planning, influencing national research directions, and your long-term goals within the organization.

As you prepare for these interviews, consider the following questions that may arise during the process.

Software Engineering Institute Research Scientist Interview Questions

In this section, we’ll review the various interview questions that might be asked during a Research Scientist interview at the Software Engineering Institute. The interview will focus on your expertise in applied artificial intelligence, machine learning, and your ability to collaborate and lead research initiatives. Be prepared to discuss your past research experiences, technical skills, and how you can contribute to the mission of the SEI.

Machine Learning and AI

1. Can you describe a machine learning project you led and the impact it had?

This question aims to assess your hands-on experience and leadership in machine learning projects.

How to Answer

Discuss the project scope, your role, the methodologies used, and the outcomes. Highlight any innovative approaches you took and the impact on stakeholders.

Example

“I led a project focused on developing a predictive maintenance model for military equipment. By utilizing a combination of supervised learning algorithms, we reduced downtime by 30%, which significantly improved operational efficiency. The model was later adopted across multiple departments, showcasing its effectiveness.”

2. How do you approach adversarial machine learning?

This question evaluates your understanding of security in AI systems.

How to Answer

Explain your knowledge of adversarial attacks and defenses, and provide examples of how you have addressed these challenges in your work.

Example

“I approach adversarial machine learning by first identifying potential vulnerabilities in the model. In a recent project, I implemented adversarial training techniques that improved the model's robustness against specific attack vectors, resulting in a 25% increase in accuracy under adversarial conditions.”

3. What techniques do you use for feature selection in your models?

This question assesses your technical skills in model optimization.

How to Answer

Discuss various techniques you have used, such as recursive feature elimination, LASSO, or tree-based methods, and explain why you chose them.

Example

“I often use recursive feature elimination combined with cross-validation to ensure that the selected features contribute significantly to the model's performance. In a recent project, this approach helped reduce the feature set by 40% while maintaining model accuracy.”

4. Describe your experience with deep learning frameworks.

This question gauges your familiarity with tools and technologies in machine learning.

How to Answer

Mention specific frameworks you have used, such as TensorFlow or PyTorch, and describe a project where you applied them.

Example

“I have extensive experience with TensorFlow, particularly in developing convolutional neural networks for image classification tasks. In one project, I implemented a CNN that achieved a 95% accuracy rate on a challenging dataset, which was later published in a peer-reviewed journal.”

5. How do you stay updated with the latest trends in AI and machine learning?

This question evaluates your commitment to continuous learning in a rapidly evolving field.

How to Answer

Discuss the resources you use, such as academic journals, conferences, or online courses, and how you apply new knowledge to your work.

Example

“I regularly read journals like the Journal of Machine Learning Research and attend conferences such as NeurIPS. Recently, I applied insights from a workshop on reinforcement learning to enhance a project focused on autonomous systems.”

Collaboration and Communication

1. Describe a time when you had to collaborate with a diverse team.

This question assesses your teamwork and interpersonal skills.

How to Answer

Share an example that highlights your ability to work with individuals from different backgrounds and expertise.

Example

“I worked on a project with a team of software developers, data scientists, and military personnel. I facilitated regular meetings to ensure everyone’s input was valued, which led to a more comprehensive solution that met both technical and operational needs.”

2. How do you communicate complex technical concepts to non-technical stakeholders?

This question evaluates your communication skills.

How to Answer

Explain your approach to simplifying complex ideas and providing relevant context for your audience.

Example

“I focus on using analogies and visual aids to explain complex concepts. For instance, when presenting a machine learning model to a government client, I used a simple analogy comparing the model to a decision-making process, which helped them understand its functionality and benefits.”

3. Can you give an example of how you mentored a junior researcher?

This question assesses your leadership and mentoring abilities.

How to Answer

Describe the mentoring experience, the challenges faced, and the outcomes of your guidance.

Example

“I mentored a junior researcher on a project involving natural language processing. I provided guidance on best practices for data preprocessing and model evaluation, which helped them successfully publish their first paper on the topic.”

4. How do you handle conflicts within a research team?

This question evaluates your conflict resolution skills.

How to Answer

Discuss your approach to addressing conflicts, emphasizing communication and collaboration.

Example

“When conflicts arise, I encourage open dialogue to understand different perspectives. In one instance, I facilitated a meeting where team members could express their concerns, leading to a compromise that improved our project’s direction.”

5. What strategies do you use to ensure your research aligns with government needs?

This question assesses your understanding of stakeholder requirements.

How to Answer

Explain how you gather requirements and feedback from stakeholders to guide your research.

Example

“I regularly engage with government stakeholders to understand their challenges and needs. By conducting interviews and surveys, I ensure that my research is relevant and can be effectively transitioned into operational capabilities.”

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Write a function to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list. Bonus: Determine the time complexity.

• Write a function missing_number to find the missing number in an array. You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of (O(n)) required.

• Write a function precision_recall to calculate precision and recall metrics from a 2-D matrix. Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).

• Write a function to search for a target value in a rotated sorted array. Suppose an array sorted in ascending order is rotated at some pivot unknown to you beforehand. Write a function to search for a target value in the array and return its index; otherwise, return -1. Bonus: Your algorithm's runtime complexity should be in the order of (O(\log n)).

• Would you think there was anything fishy about the results of an A/B test with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with these results?

• How would you set up an A/B test to optimize button color and position for higher click-through rates? A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• What would you do if friend requests on Facebook are down 10%? A product manager at Facebook reports a 10% decrease in friend requests. What steps would you take to address this issue?

• Why might the number of job applicants be decreasing while job postings remain constant? You observe that the number of job postings per day has remained stable, but the number of applicants has been decreasing. What could be causing this trend?

• What are the drawbacks of the given student test score datasets, and how would you reformat them for better analysis? You have data on student test scores in two different layouts. What are the drawbacks of these formats, and what changes would you make to improve their usefulness for analysis? Additionally, describe common problems in "messy" datasets.

• Is this a fair coin? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair based on this outcome.

• Write a function to calculate sample variance from a list of integers. Create a function that takes a list of integers and returns the sample variance, rounded to 2 decimal places. Example input: test_list = [6, 7, 3, 9, 10, 15]. Example output: get_variance(test_list) -> 13.89.

• Is there anything suspicious about the A/B test results with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Evaluate if there is anything suspicious about these results.

• How to find the median in a list where over 50% of elements are the same? Given a sorted list of integers where more than 50% of the list is the same integer, write a function to return the median value in (O(1)) computational time and space. Example input: li = [1,2,2]. Example output: median(li) -> 2.

• What are the drawbacks of the given student test score data layouts? You have student test score data in two different layouts. Identify the drawbacks of these layouts, suggest formatting changes for better analysis, and describe common problems in "messy" datasets.

• How would you evaluate whether using a decision tree algorithm is the correct model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will pay back a personal loan. How would you evaluate if a decision tree is the right choice, and how would you assess its performance before and after deployment?

• How does random forest generate the forest, and why use it over logistic regression? Explain the process by which a random forest generates its ensemble of trees. Additionally, discuss the advantages of using random forest compared to logistic regression.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. Describe scenarios where you would prefer a bagging algorithm over a boosting algorithm, and discuss the tradeoffs between the two.

• How would you justify using a neural network for a business problem and explain its predictions to non-technical stakeholders? Your manager asks you to build a neural network model to solve a business problem. How would you justify the complexity of this model and explain its predictions to non-technical stakeholders?

• What metrics would you use to track the accuracy and validity of a spam classifier? You are tasked with building a spam classifier for emails and have completed a V1 of the model. What metrics would you use to evaluate the model's accuracy and validity?

Are you passionate about shaping the future of technology and national security? The Software Engineering Institute (SEI) at Carnegie Mellon University offers a dynamic environment where you can collaborate with elite researchers and faculty to tackle groundbreaking challenges in quantum communication, computing, and machine learning. As a Research Scientist, you will contribute to projects that have a lasting impact on national security strategies, working within interdisciplinary teams to develop innovative solutions and publish your findings in prestigious platforms.

If you want more insights about the company, check out our main Software Engineering Institute Interview Guide, where we have covered many interview questions that could be asked. At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!