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user@intervues:~/experiences/…$
Level: Senior-Level
Round: Onsite · Type: Multiple Types · Difficulty: 6/10 · Duration: 120 min · Interviewer: Unfriendly
Topics: Behavioral, System Design, REST API, GraphQL, JavaScript, Database Schema, ML Model Monitoring, Data Drift, Data Quality, Time Series Data
Location: Los Angeles, CA, US
Interview date: 2026-01-15
This was my onsite interview. Because I passed the VO1, they scheduled the VO2 (onsite).
Round 1: I spoke with a manager from the team I was interviewing with. This round was purely behavioral, mainly discussing Netflix's culture. check https://jobs.netflix.com/culture
Round 2: This was a full-stack/front-end design round, which I didn't perform well in. I don't have much front-end experience. Originally, I applied for an infra role, but was told that the position was no longer available. They mentioned a team building a web portal for ML engineers, essentially a backend engineer role writing web applications, designing database schemas, and building UIs. The recruiter told me about this round beforehand. I was hesitant but proceeded with the interview.
The question was to build an MLP Portal, a web app to provide a unified ML experience for MLEs/data scientists. This would involve recording experimentation, registering a model, deploying the model, promoting the model to production, and monitoring the models – similar to an enhanced MLflow.
I was asked to design REST APIs and a database schema, and was also asked about GraphQL and JavaScript. This round should be straightforward for a full-stack developer. I haven't worked on front-end in a while, so I didn't explain it well.
Even though I didn't answer the front-end questions well, I recovered in the ML area.
I discussed model monitoring techniques, such as calculating data drift, data quality, percent empty, and PSI. I also discussed how to set up alerts and what backend to use for querying time-series data. The interviewer seemed satisfied with this.