6 model serving engineer jobs at 2 companies in Carson, CA
🚀PromotedHiringCafe
ML Engineer - Inference & Model Deployment
Cupertino, CA, US
$250k-$310k/yrOn-SiteFull Time
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Turn powerful AI and ML models into fast, reliable production systems. Own inference latency, throughput, model-serving architecture, multi-GPU systems, and production deployment for millions of users.
Distributed Systems Engineer 5 - Decisioning & Optimization
New York or Los Angeles or Los Gatos or Seattle
$388k-$619k/yrOnsiteFull Time
NetflixNASDAQ: NFLX: Global video streaming and media production service.
7+ YOE7+ years building distributed systems; ads domain experience; ML model serving; backend APIs and ad tech systems; low-latency serving; collaboration across teams.
ML model serving, real-time inference, APIs, ad servers, bidders, pacing, routing, calibration serving
Distributed Systems Engineer 6 - Decisioning & Optimization
New York City or Seattle or Los Angeles or Los Gatos
$499k-$900k/yrOnsiteFull Time
NetflixNASDAQ: NFLX: Provider of global streaming entertainment and video content.
10+ YOE10+ years building large-scale distributed systems (3+ years in ads); expertise in ML model serving with sub-20ms P99, ad serving/bidding/pacing systems, API and platform design, technical leadership, and cross-functional collaboration.
New York City or Seattle or Los Angeles or Los Gatos
$466k-$750k/yrOnsiteFull Time
NetflixNASDAQ: NFLX: Provider of global streaming entertainment and video content.
7+ YOE7+ years software engineering experience with 3+ years on ML infrastructure or model serving; proficiency in Java, Python, or Scala; experience building high‑QPS, low‑latency model serving, feature serving, and model monitoring.
NetflixNASDAQ: NFLX: Global video streaming and media production service.
7+ YOE7+ years software engineering; 3+ years ML infrastructure, model serving, or ML platform experience in ads/real-time decisioning; real-time model serving with sub-20ms latency; proficiency in Java, Python, or Scala; experience with ML serving frameworks and real-time feature pipelines; strong model monitoring and production readiness.
Java, Python, Scala, ML serving frameworks, feature stores, model registries
Pronoia Energy: Developing room-temperature macroscopic quantum energy storage technology.
Proven production experience shipping agent or tool-use systems, experience self-hosting open-weights models on GPUs, strong orchestration/serving/evaluation skills, and habit of treating hallucination as engineering problem.