Roblox Senior ML Engineer, Ads — ad ranking from the ground up

Interview prep for Roblox's Senior Machine Learning Engineer role on the Ads team, building ranking and recommendation models for a performance-advertising platform that's still early-stage. Expect deep technical dives into large-scale recommendation/ranking systems, transformer-based modeling, and cross-team technical leadership. Strong prep for senior ML engineering interviews focused on ads/recommendation systems at scale.

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What this interview tests

Large-scale ad ranking and recommendation model design
Transformer-based model training, inference, and product integration
ML system design under real production constraints (latency, scale, serving)
Cross-team technical leadership and decision-making
Translating research ideas into shippable, business-impacting features

Common question themes

Design a large-scale ad ranking or recommendation model — walk through the full pipeline

Tell me about a transformer-based model you took from training to production

Describe a hard technical decision you drove across multiple teams or orgs

How do you balance research exploration with shipping practical improvements

How do you evaluate whether an ML change actually improved ad performance or advertiser value

How candidates describe it

Real Senior Machine Learning Engineer interview stories — retold from candidates' public write-ups, with sources.

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