Partner with product, data science, and infrastructure leaders to deeply understand their priorities and translate them into clear technical strategies.
Balance partner needs by designing solutions that advance user-facing experiences while ensuring system scalability, reliability, and efficiency.
Oversee the delivery of end-to-end improvements in search quality, spanning data pipelines, ML models, and distributed systems.
Drive the adoption of advanced ML methods while ensuring pragmatic, production-ready implementations.
Grow, mentor, and develop a diverse team of engineers, fostering collaboration with applied scientists and system experts.
Provide technical and organizational leadership, ensuring execution excellence while crafting a long-term strategy for search and knowledge systems.
5+ years of experience in leading engineering/applied research/ML experiences in natural language processing, SOTA generative AI models
Proven record of consistent delivery of technology/products across the full Machine Learning life cycle
MS or Ph.D. in Computer Science, Machine Learning, information retrieval, data mining, or a related field
Proven background in Machine Learning, NLP, and large-scale Search, with the ability to guide teams at the forefront of these fields.
Deep expertise in retrieval and ranking models and the broader search stack, with a track record of delivering production-quality systems at scale.
Strong engineering leadership and fundamentals, with experience building and mentoring high-performing teams.
Excellent product vision and sound business judgment; able to balance long-term strategy with short-term deliverables.
Exceptional communication and collaboration skills, with the ability to align cross-functional stakeholders (product, data science, infrastructure) around shared goals.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.