Software Engineer, ML Infrastructure, Level 4

Overview In this role, you will design and optimize scalable ML infrastructure to improve Snapchat’s ranking and recommendations. You will work with cross-functional teams to deploy models and build data pipelines for online inference and offline training. You’ll create high-performance inference systems and cloud-based training infrastructure, ensuring reliability and efficiency. You’ll contribute to data management and evaluation processes, advancing production-ready ML capabilities. This is a hands-on role at a fast-paced company committed to privacy and impactful technology. Compensation / Benefitspaid parental leavecomprehensive medical coverageemotional and mental health supportequity in RSUslong-term incentive compensation ResponsibilitiesDesign and optimize infrastructure systems for ML workloads at scale to improve reliability and efficiency across Snapchat’s ML infrastructureBuild and enhance feature generation and serving pipelines for online inference and offline data generationDevelop high-performance inference systems for fast, efficient AI model servingBuild scalable ML model training, evaluation, and inference infrastructure in the cloudDevelop comprehensive data management systems for scalable data collection, labeling, processing, and evaluationCollaborate with ML engineers to deploy cutting-edge models into productionLeverage AI tools and rapid engineering workflows to ship scalable services with robust code quality, security, and production readiness Key requirementsStrong programming skills in Python, Java, Scala or C++Strong problem-solving skills with focus on performance, scalability, and efficiencyGood understanding of distributed systems and large-scale ML infrastructureExperience with big data processing frameworks such as Spark, Flink, or RayAbility to collaborate effectively with othersProven track record operating highly-available systems at scaleAbility to proactively learn and apply new concepts in AI systemsAdaptability in applying evolving AI tools and practicesBachelor’s degree in a technical field and relevant work experience2+ years post-Bachelor’s software development experience (or equivalent combinations)collaborationproactive learningproblem-solvingPythonJavaScala