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Interview Questions
Practice with real questions asked in interviews. Click any card to reveal the answer.
Technical Questions
Product of Array Except Self - Return an array where each element is the product of all other elements
Approach & Solution
Approach: Consider time/space complexity, edge cases, and explain your thought process clearly. Sign up to access detailed solutions!
LRU Cache - Design a data structure for Least Recently Used cache
Approach & Solution
Approach: Consider time/space complexity, edge cases, and explain your thought process clearly. Sign up to access detailed solutions!
Rotate Image - Rotate an N x N matrix by 90 degrees clockwise in-place
Approach & Solution
Approach: Consider time/space complexity, edge cases, and explain your thought process clearly. Sign up to access detailed solutions!
Behavioral Questions
How do you handle tight deadlines and pressure?
Sample Answer (STAR Method)
Task: I needed to manage my time effectively to complete everything without compromising quality.
Action: I started by listing all tasks and estimating time for each. I prioritized based on due dates and complexity, then created a detailed schedule with specific time blocks. I eliminated distractions by working in the library, used the Pomodoro Technique for focused coding sessions, and took strategic breaks to avoid burnout. When I realized one assignment was taking longer than expected, I reached out to the TA for clarification rather than spending hours debugging alone.
Result: I completed all assignments on time and performed well on my exams. This experience taught me the importance of planning, prioritization, and knowing when to seek help. I now proactively manage my schedule to avoid such situations, but I'm confident in my ability to perform under pressure when necessary.
Give an example of when you had to make a difficult trade-off decision
Sample Answer (STAR Method)
Task: I needed to decide which feature to prioritize, as we only had time to properly implement one.
Action: I analyzed user feedback from our beta testers and found that 80% of users mentioned wanting notifications, while only 30% mentioned search filters. I presented data to the team showing that notifications would provide more value. I also proposed a simpler basic search that we could implement in 2 days, allowing us to deliver both features in limited form.
Result: We implemented full notification functionality and basic search. User satisfaction scores in our final presentation were 4.5/5. This taught me to make data-driven decisions focused on user needs, and to look for creative solutions that don't require choosing between extremes.
Meta Meta Research Scientist Intern - 3D Scene Reconstruction / Generative AI - PhD Interview Questions Interview Process 2026
The Meta Meta Research Scientist Intern - 3D Scene Reconstruction / Generative AI - PhD Interview Questions interview typically consists of 350+ technical questions covering algorithms, data structures, and system design. Located in Remote, this position offers hands-on experience with cutting-edge technology and mentorship from senior engineers.
Key interview stages include: initial screening, technical coding rounds focusing on Data Structures, System Design, Behavioral, and final rounds with team leads. The difficulty level is rated as Hardwithin the FAANG tier.
Essential Skills for Meta Meta Research Scientist Intern - 3D Scene Reconstruction / Generative AI - PhD Interview Questions Role
Technical Skills
- Machine Learning
- Python
- TensorFlow/PyTorch
- Statistics
Interview Topics
- Data Structures
- System Design
- Behavioral
What Makes Meta Different
Meta is known for its rigorous technical standards and innovative culture. Interns work on real production systems and contribute to projects used by millions of users.
The company offers comprehensive learning opportunities, including mentorship programs, technical talks, and hands-on experience with industry-leading tools and frameworks.Meta Research Scientist Intern - 3D Scene Reconstruction / Generative AI - PhD Interview Questions interns typically work in Remote with hybrid flexibility.
Frequently Asked Questions
How difficult is the Meta Meta Research Scientist Intern - 3D Scene Reconstruction / Generative AI - PhD Interview Questions interview?
The interview is rated as Hard difficulty. Candidates should prepare for 350+ practice questions covering algorithms, data structures, and system design fundamentals.
What programming languages are accepted?
Most candidates use Python, Java, C++, or JavaScript. Choose the language you're most comfortable with for optimal performance during coding rounds.
How long is the Meta interview process?
The process typically takes 2-4 weeks from initial application to final decision, including phone screens, technical rounds, and team interviews.
Meta Meta Research Scientist Intern - 3D Scene Reconstruction / Generative AI - PhD Interview Questions salary and benefits
Meta offers competitive compensation packages for Meta Research Scientist Intern - 3D Scene Reconstruction / Generative AI - PhD Interview Questions positions in Remote. Benefits include health insurance, learning stipends, mentorship programs, and potential full-time conversion opportunities.
Best preparation resources for Meta interviews
Practice coding problems on LeetCode, study system design fundamentals, review computer science concepts, and prepare behavioral questions using the STAR method. Focus on Data Structures, System Design, Behavioral.
Meta Internship Program 2026
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