Machine Learning Engineer

• Set and execute the technical roadmap for Generative Insights and Predictive Experimentation from prototypes through production adoption
• Build cross-experiment learning systems that retrieve and synthesize historical experiments, detect recurring effects and segment behavior, reanalyze prior results, and generate evidence-backed hypotheses
• Develop predictive models and simulation workflows to estimate likely impact, affected segments, regression risk, and uncertainty before live experiments
• Create datasets and feature or retrieval pipelines from exposures, events, metrics, experiment metadata, and replay data
• Establish evaluation through offline benchmarks, backtests, calibration, drift monitoring, prediction-to-outcome comparisons, and explicit failure or abstention behavior
• Turn models into product, API, and agent workflows supporting experiment design, approval-gated action, and measured learning
• Partner with data science and product teams on experiment design, causal inference, sequential decision-making, variance reduction, and prediction versus causal evidence
• Build reliable services and intuitive workflows for high-stakes product decisions
• Provide technical leadership across engineering, product, data science, and research partners
• Raise production ML quality across the experimentation platform
• Collaborate with teams building ChatGPT, Codex, model measurement workflows, consumer products, Growth, business subscription experiences, developer products, and shared infrastructure

Machine Learning Engineer, Core Experimentation

• Design and optimize infrastructure systems for machine learning workloads at scale
• Drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
• Develop high-performance inference systems for fast and efficient AI model serving
• Build cloud infrastructure for scalable ML model training, evaluation, and inference
• Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
• Work on state-of-the-art vector search algorithms to improve retrieval-system precision, recall, and scalability
• Collaborate with ML engineers to deploy cutting-edge models into production

Machine Learning Engineer jobs in Washington

Machine Learning Engineer, Core Experimentation

Software Engineer, ML Infrastructure