Design, develop, and maintain advanced search ranking models, leveraging machine learning techniques such as label collection, personalized ranking, candidate retrieval, user behavior analysis, & LLM’s
Explore and implement robust query understanding functionality, document understanding, user preference understanding, and low latency transformer-based architectures to improve search relevance
Collaborate with cross-functional teams to align research goals with business needs and ensure successful deployment of innovative search solutions into production.
Build and manage large-scale search datasets, including corpora, relevance labels, and user interactions, utilizing tools and techniques for data collection, cleaning, and preprocessing.
Conduct thorough evaluations of search models using industry-standard metrics, analyze results, and provide insights for model improvement and business strategy.
Stay up-to-date with the latest trends in ML, search science, RecSys, and information retrieval, frequently attending conferences, workshops, and engaging in collaborative research projects.
Contribute to Coursera’s research efforts by publishing in top-tier conferences such as SIGIR, WWW, CIKM, and similar venues.
Requirements & Skills:
PhD or Master’s degree in Computer Science, Information Retrieval, or closely related fields.
Demonstrated experience in developing advanced search models, and recommender systems, incorporating techniques like natural language processing (NLP) and learning-to-rank algorithms.
Familiarity with information retrieval metrics, evaluation methodologies, and scalable search system architecture.
Track record of publishing research in top-tier conferences such as RecSys, SIGIR, EMNLP, WWW, CIKM, or similar venues.
Proficiency in programming languages and deep learning frameworks such as Python, TensorFlow, or PyTorch.
Experience in working with large-scale search datasets and tools for data collection, cleaning, and preprocessing.
Familiarity with ML deployment in production environments and tools for version control, such as Git.
Proven ability to stay current with emerging research and technologies in the ML, search science, or recommender systems domain.
Experience collaborating with cross-functional teams and excellent communication abilities.
Passion for driving impact in the field of online education through innovative ML and search science techniques.
Familiarity with Coursera’s platform and course offerings, as well as active participation in wider AI and Machine Learning communities, is a plus.
