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You will also own the full lifecycle of ML-powered features: from prototyping and experimentation through launch, monitoring, and iteration.</p>\n<p>A Typical Day:</p>\n<ul>\n<li>Design, build, and operate the systems that serve ML models within the messaging stack, with a focus on latency, reliability, and scalability</li>\n<li>Write and review technical designs that solve large, open-ended problems at the intersection of ML and product engineering without clearly-known solutions</li>\n<li>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</li>\n<li>Collaborate with other engineers and cross-functional partners across Messaging, Trust &amp; Safety, Localization, and Platform organizations to align on long-term technical solutions</li>\n<li>Mentor, guide, advocate, and support the career growth of individual contributors</li>\n<li>Establish engineering standards for ML integration across the messaging surface, including feature flagging, A/B testing, observability, and graceful degradation</li>\n</ul>\n<p>Your Expertise:</p>\n<ul>\n<li>9+ years of relevant engineering hands-on work experience</li>\n<li>Bachelors, Masters, or PhD in CS or related field</li>\n<li>Demonstrated experience building and shipping ML-powered product features in production environments, including model serving, feature pipelines, online/offline evaluation, and monitoring</li>\n<li>Exceptional architecture abilities and experience with architectural patterns of large, high-scale applications</li>\n<li>Familiarity with NLP/NLU techniques and large language models, particularly as applied to messaging, conversational AI, or content understanding</li>\n<li>Shipped several large-scale projects with multiple dependencies across teams, specifically at the intersection of ML infrastructure and product engineering</li>\n<li>Technical leadership and strong communication skills with the ability to translate between ML research, product goals, and engineering execution</li>\n<li>Experience operating distributed, real-time systems at scale with high reliability requirements</li>\n<li>Experience with real-time messaging systems or event-driven architectures</li>\n<li>Familiarity with ML infrastructure at scale (e.g., feature stores, model registries, online inference platforms)</li>\n<li>Prior work on trust &amp; safety, content moderation, or internationalization in a messaging context</li>\n<li>Experience with LLM-based product features, including prompt engineering, retrieval-augmented generation, or fine-tuning</li>\n</ul>\n<p>How We&#39;ll Take Care of You:</p>\n<p>Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. 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As the first security hire, you will build out our security operations and vulnerability management process for our AI gateway platform. You&#39;ll implement programs, run tooling, ship security fixes, and drive remediation across our stack. You’ll be responsible for all aspects of ensuring the security of our platform and users. This isn&#39;t a compliance paperwork role; it&#39;s a hands-on security position with direct impact on how we protect millions of API requests daily. You&#39;ll work closely with engineering and senior leadership to ship security improvements that actually matter.</p>\n<p><strong>What You&#39;ll Do</strong></p>\n<ul>\n<li>Deploy and operate vulnerability scanning across our cloud infrastructure. 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