Watch Netflix movies & TV shows online or stream right to your smart TV, game console, PC, Mac, mobile, tablet and more. Backed by IVP and Redpoint.
About the role
Build and operate end-to-end ML model serving infrastructure for real-time ad decisioning: model publishing, packaging, validation, deployment into the serving stack with zero-downtime hot-swap Scale the inference path to support dozens of concurrent models on every ad request at 1M+ QPS with strict latency budgets, including batching strategies, CPU/GPU allocation, model versioning, and fallback tiers
What they're looking for
- 7+ years of software engineering experience, 3+ years focused on ML infrastructure, model serving, or ML platform work in an ads or real-time decisioning context
- Built and operated real-time model serving systems at high QPS with sub-20ms latency: online inference, feature stores, model registries, model hot-swap, canary and shadow rollout
- Proficiency in Java, Python, or Scala with a solid understanding of multi-threading, memory management, and performance optimization for latency-critical paths
- Hands-on with ML serving frameworks: serialization, runtime optimization, and deployment constraints
- Experience with feature engineering pipelines for real-time systems: online/offline consistency, hydration strategies, caching, and freshness tradeoffs
- Strong understanding of model monitoring in production: drift detection, prediction distribution analysis, calibration, and latency profiling
More about this role
At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
We launched a new ad-supported tier in November 2022 and are building an in-house world-class ad tech ecosystem to offer our members more choices in consuming their content. Our new tier allows us to attract new members at a lower price point while also creating a compelling path for advertisers to reach deeply engaged audiences.
The Decisioning & Optimization engineering team owns the systems that determine which ad wins every impression, at what price, and how campaign budgets deliver across all inventory surfaces. Our work spans three platform areas:
ML infrastructure for model serving : real-time inference at 1M+ QPS, multi-model parallel evaluation, feature hydration, model lifecycle from canary deployment through production monitoring
Auction, ranking, and scoring : multi-stage candidate selection,...
Browse similar: AI jobs · AI startup jobs · Startup jobs