LinkedIn AI Engineer Interview Experiences 2026

Real, anonymous reports from people who interviewed for AI Engineer at LinkedIn, newest first and distilled into what to expect across the loop.

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4 months ago

Difficult Negative United States

My process started with a 30-minute HR phone screening. After that, about a week later, I had a scheduled 1-hour technical screen that felt very LeetCode-style—coding problems where the main goal was to implement cleanly and correctly.

Once I passed, I moved into a virtual onsite that was intense: four back-to-back rounds. Each round leaned on a mix of what I’d done before and how I thought about ML—talking through past experience, then diving into different ML topics and algorithms. The pace was fast enough that I spent a lot of energy keeping my explanations structured while still getting the technical details right.

4 months ago

Average Neutral San Francisco, CA

I first went through recruiter screening, and then I had a technical screen where I had to code the K-Nearest Neighbors algorithm from scratch in Python. It wasn’t just recalling an approach—I had to build it out and get the mechanics correct.

After that, I landed in the final loop with five rounds that all ran back-to-back. The rounds covered an AI coding segment, a system design round, a DSA round, an AI/ML round, and then a hiring manager conversation. Even though the topics shifted, the through-line was how I reasoned through algorithms and how I connected implementation details back to ML concepts.

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What to expect

Distilled from the reports

Recruiter Screening

The interview process typically begins with a brief recruiter screening call, where candidates discuss their experience and the overall interview structure. This initial interaction sets the tone for the subsequent technical rounds.

Recruiter callInterview structureExperience discussion

Technical Coding Screen

Candidates face a technical screen that often includes LeetCode-style coding problems and may also touch on ML fundamentals or system design. Success in this round is critical to advancing to the onsite interviews.

LeetCodeTechnical screenCoding problems

Virtual Onsite Format

The virtual onsite consists of multiple back-to-back rounds, typically five, covering a mix of AI coding, system design, and ML theory. Candidates should prepare for a fast-paced environment that tests both implementation skills and conceptual understanding.

Virtual onsiteMultiple roundsAI coding

Focus on ML Fundamentals

Throughout the interview process, there is a strong emphasis on machine learning concepts, including algorithms, statistics, and mathematical foundations. Candidates should be ready to explain these concepts clearly and relate them to practical coding scenarios.

ML conceptsStatisticsMathematical foundations

Behavioral and Technical Integration

Behavioral rounds may delve deeper into technical discussions than expected, often exploring candidates' past experiences and technical knowledge. This integration requires candidates to be prepared for technical questions even in behavioral contexts.

Behavioral roundTechnical depthExperience exploration

Overall Difficulty and Feedback

Candidates generally find the interview loop to be of average to high difficulty, with a clear structure but sometimes inconsistent feedback. Even strong performances in certain areas may not guarantee an offer, highlighting the need for broad preparation.

Difficulty levelFeedback consistencyBroad preparation