• Design, build, and operate the systems that serve ML models within the messaging stack, with a focus on latency, reliability, and scalability • Write and review technical designs that solve large, open-ended problems at the intersection of ML and product engineering without clearly-known solutions • Partner with ML, data science, and product teams to identify high-value opportunities, establish evaluation criteria, and close the gap between offline model performance and production impact • Collaborate with other engineers and cross-functional partners across Messaging, Trust & Safety, Localization, and Platform organizations to align on long-term technical solutions • Mentor, guide, advocate, and support the career growth of individual contributors • Establish engineering standards for ML integration across the messaging surface, including feature flagging, A/B testing, observability, and graceful degradation

• Developing a highly optimized inference framework running on the world’s largest supercomputers and data centers • Collaborate on innovative, next-generation products at the forefront of technology in terms of performance, scalability, and features

• Collaborate with data analysts to spec and build features that draw new customers to our product. • Provide a backend to our mobile and web frontends. • Build admin tools to increase efficiency of day-to-day support operations. • Integrate with third-party APIs. • Work on a beautiful app with high standards for UI. • Prevent errors using TypeScript's advanced static typing features. • Exercise ownership over the product and contribute ideas for improvement.

• Research and translate emerging AI findings into practical recommendations for engineering teams • Design, prototype, and iterate on resources, experiments, or workflows for AI integration • Build or improve infrastructure supporting AI usage • Analyze AI usage patterns to generate insights for tooling or training improvements • Partner cross-functionally to scale AI capabilities across engineering