Currently tracking 50 active AI roles, with 144 new openings in the last 4 weeks. Primary focus: Ship · Engineering. Salary range $131k–$1500k (avg $604k).
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Engineer 5 - Globalization Machine Learning Engineer at Netflix focused on optimizing training and inference efficiency for LLMs and Multimodal LLMs within the Globalization team. The role involves designing and building scalable systems, optimizing data pipelines, distributed training, mixed precision, KV cache, batching, and quantization to improve performance, latency, and reliability of ML models for Netflix's global catalog. | ServePost-train | 8 |
| Distributed Systems Engineer 6 - Decisioning & Optimization Netflix is seeking a Distributed Systems Engineer 6 to lead the technical direction of the Decisioning & Optimization team within their ad tech ecosystem. This role involves architecting and scaling real-time ad decisioning systems, including ML model serving infrastructure, ranking, scoring, and optimization under strict latency constraints. The engineer will also drive operational excellence and collaborate with Science and Platform teams to productionize ML algorithms. |
| ServeAgent |
| 7 |
| Machine Learning Engineer (L4/L5) - Emerging Game Technologies Machine Learning Engineer focused on MLOps, deployment, and performance optimization for AI-driven game concepts, bridging research and production for cloud and edge environments. | Serve | 7 |
| Machine Learning Engineer 5 - Ads Inventory Management & Forecasting Machine Learning Engineer at Netflix focused on Ads Inventory Management & Forecasting. The role involves building end-to-end ML model deployment and inference infrastructure for low-latency real-time ad systems, handling large data volumes with Spark, and productionizing predictive models for campaign effectiveness forecasting. It also includes building scalable simulation solutions for inventory scenarios and collaborating with cross-functional teams. | ServeData | 7 |
| Machine Learning Engineer 5 - Ads Platform Engineering Netflix is hiring Machine Learning Engineers for their Ads Platform Engineering teams. The role involves building and deploying ML models for low-latency real-time ad systems, focusing on areas like inventory forecasting, ad serving, programmatic interfaces, member experience, and audience targeting. Responsibilities include developing and productionizing predictive models for campaign effectiveness, yield optimization, bid ranking, and dynamic allocation, as well as building scalable simulation solutions. Experience with big data tools like Spark and proficiency in languages like Java, C++, Python, or Scala are required. | ServeAgent | 7 |
| Software Engineer L4/L5, Model Serving Systems, Machine Learning Platform Netflix is seeking a Software Engineer for their Machine Learning Platform team to develop and expand their model serving systems, focusing on infrastructure for LLMs and other large foundation models. The role involves building scalable, robust systems for online ML model inference, optimizing for latency and cost, and ensuring high availability and performance. This is a highly cross-functional role partnering with various engineering and data science teams. | ServeAgent | 7 |
| Distributed Systems Engineer 5 - Decisioning & Optimization Netflix is seeking a Distributed Systems Engineer to build and scale the core infrastructure for their ad tech ecosystem, focusing on real-time ad decisioning, ML model serving, and optimization systems. The role involves working across the stack from model serving to auction execution and pacing, shipping production systems that directly impact revenue and advertiser outcomes. | ServeAgent | 5 |