About the job
As the Director of Algorithms within Ads Engineering, you will be the driving force behind the intelligence engine that powers Apple's advertising ecosystem. You will lead a multidisciplinary organization of engineering managers, applied scientists, ML engineers, and systems engineers -- setting the vision, shaping the roadmap, and delivering at the intersection of cutting-edge research and production-scale engineering.
Responsibilities
Define the strategic vision and technical roadmap for the entire algorithms funnel, delivering intelligence across all phases of ads delivery -- including retrieval, ranking, matching, auction, and budget optimization models.
Champion algorithm engineering excellence end-to-end across a complex production ecosystem, partnering with infrastructure, serving, privacy, and experimentation teams to translate state-of-the-art models into reliable, customer-facing capabilities.
Drive clear execution plans across organizational boundaries, balancing research innovation with operational excellence, launch readiness, and production reliability.
Partner deeply with Ads Product leaders to co-drive marketplace strategy and translate business objectives into algorithmic systems that optimize advertiser outcomes, user relevance, auction efficiency, and long-term marketplace health.
Partner closely with Data Insights and experimentation teams to define success metrics, measurement frameworks, and evaluation strategies that ground algorithmic decisions in rigorous, transparent experimentation.
Mentor and grow your management team while providing guidance to senior technical ICs.
Qualifications
Minimum
15+ years of professional experience in Machine Learning, Applied Science, or Software Engineering, with a strong focus on performance advertising, search, or recommendation systems.
10+ years of engineering leadership experience, including a proven track record of managing other managers as well as senior/staff-level individual contributors.
Deep technical expertise across the entire algorithms funnel, including signals processing, candidate matching, predictive modeling (e.g., CTR/CVR), and ranking.
Experience with modern techniques using embeddings, transformer architectures, distillation methods, and reinforcement learning based methods.
Extensive experience in algorithm engineering, with a strong understanding of how to build, deploy, and scale high-throughput, low-latency ML systems in production environments.
Exceptional communication and diplomatic skills, with the ability to build consensus, navigate complex cross-functional relationships, and articulate technical strategies to both technical and non-technical stakeholders.
A demonstrated commitment to fostering an inclusive, respectful, and highly collaborative team culture that empowers individuals to do their best work.
Strong alignment with Apple's core values, particularly regarding user privacy and delivering premium user experiences.
Preferred
Experience with privacy-enhancing technologies (PETs) or building ML systems under strict privacy constraints.
Experience with Ads technology and domain.
Ph.D. or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field, accompanied by relevant industry experience.