About the role
Lead and grow a team of Applied Scientists and Machine Learning Engineers, including hiring, coaching, and developing talents across Applied Science and Engineering. Define technical vision and strategy for the end-to-end recommendation systems, spanning from recall, coarse ranking, fine-ranking to mixed reranking stages. Lead teams to build and implement next-generation recommendation systems with deep learning, LLMs, agents, and advanced recommendation techniques. Drive end-to-end execution across multiple initiatives, from ideation and design to production and iteration. Oversee system architecture and scalability, ensuring robust, efficient, extensible, and high-quality ML solutions in production. Partner cross-functionally with product, engineering, platform, and/or leadership teams to align on priorities and deliver customer impact. Mentor and elevate
the team, fostering a culture of scientific rigor, innovations, engineering excellence, collaboration, and continuous learning. Regularly communicate team progress internally and evangelize progress and opportunities to a wider audience including leadership and stakeholders. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research). 1+ year(s) of people management experience. Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 2+ years of people management experience. Demonstrated experience managing and growing ML teams, including performance management and career development. Expertise in recommendation systems, ranking models, search relevance, personalization, LLM and/or agents. Proficiency in modern ML frameworks (e.g., PyTorch, TensorFlow), data processing systems, and cloud‑scale infrastructure. Demonstrated ability to lead cross‑functional initiatives and influence technical direction across multiple teams. Solid communication skills with the ability to articulate complex technical concepts to diverse audiences. Experience with LLM‑based ranking, agentic AI, or generative AI related to recommendation or personalization. Publications in top‑tier ML/AI conferences (e.g., NeurIPS, ACL, AAAI, NAACL, ICML, KDD, WWW, RecSys, EMNLP, CIKM, etc). Solid architectural skills with experience designing and building large‑scale ML/DL systems end-to-end, distributed pipelines, and high‑throughput online services. Experience working through full product cycles from initial design to product delivery and iterations. Experience developing and designing backgrounds in multi-tiered distributed services. Experience with data structures, algorithms, asynchronous programming, and data processing. Knowledge and experience in large scale data analytics, such as Spark. Experience working with heterogeneous signals (behavioral, contextual, semantic embeddings) and multi‑objective optimization.
