Lead Data Scientist at AirOps

About AirOpsToday thousands of leading brands and agencies use AirOps to win the battle for attention with content that both humans and agents love.We’re building the platform and profession that will empower a million marketers to become modern leaders — not spectators — as AI reshapes how brands reach their audiences.We’re backed by awesome investors, including Unusual Ventures, Wing VC, Founder Collective, XFund, Village Global, and Alt Capital, and we’re building a world-class team with in-person hubs in San Francisco, New York, and Montevideo, Uruguay.About the RoleAs Lead Data Scientist at AirOps, you'll shape how brands win in AI-driven search environments through advanced machine learning and data science. This role combines technical depth with strategic thinking: you'll build production-grade ML systems that directly impact how companies create and optimize content for AI agents and improve their search visibility. You'll work at the intersection of NLP, search algorithms, and large language models to create solutions that help content teams drive measurable business results.This is a hands-on leadership position where you'll both architect systems and write code. You'll partner with product, engineering, and customer success teams to identify opportunities where ML can transform our platform's capabilities. Your work will directly influence how thousands of brands adapt to the rapidly changing search landscape where AI shapes discovery and engagement.Key ResponsibilitiesTechnical Leadership: Design and deploy end-to-end machine learning systems including NLP models, search and recommendation algorithms, and LLM-based applications. Search and Content Intelligence: Build ML systems that analyze AI search behavior, identify content opportunities, and predict performance across different AI-driven platforms. Create algorithms that help brands understand and optimize for how AI agents discover and rank content.Cross-functional Partnership: Collaborate with product managers to translate business requirements into technical solutions.Qualifications5+ years building production machine learning systems with demonstrated business impact; strong background in NLP and search/recommendation systems requiredDeep expertise across ML approaches: classical models (XGBoost, random forests), modern deep learning architectures (transformers, graph neural networks), and reinforcement learning systemsProven ability to take models from research to production, including optimization for latency and cost at scaleExperience with ML infrastructure and tooling: model serving frameworks, experiment tracking, feature stores, and monitoring systemsTrack record of technical leadership: influencing architecture decisions, improving team practices, and driving cross-functional projects without direct authorityExcellent communication skills with ability to explain complex technical concepts to non-technical stakeholders and align ML initiatives with business outcomesOur Guiding PrinciplesExtreme OwnershipQualityCuriosity and PlayMake Our Customers HeroesRespectful CandorBenefitsEquity in a fast-growing startupCompetitive benefits package tailored to your locationFlexible time off policyGenerous parental leaveA fun-loving and (just a bit) nerdy team that loves to move fast!