Coursera can hire people in any country where we have a legal entity, assuming candidates have eligible working rights and a sufficient timezone overlap with their team. Our interviews and onboarding are conducted virtually, a part of being a remote-first company.
Coursera was launched in 2012 by two Stanford Computer Science professors, Andrew Ng and Daphne Koller, with a mission to provide universal access to world-class learning. It is now one of the largest online learning platforms in the world, with 113 million registered learners as of September 30, 2022. Coursera partners with over 275 leading university and industry partners to offer a broad catalog of content and credentials, including courses, Specializations, Professional Certificates, Guided Projects, and bachelor’s and master’s degrees. Institutions around the world use Coursera to upskill and reskill their employees, citizens, and students in fields such as data science, technology, and business. Coursera became a B Corp in February 2021.
At Coursera, our Data Science team is helping build the future of education through data-driven decision making and data-powered products. We drive product and business strategy through measurement, experimentation, and causal inference. We define, develop, and launch the models and algorithms that power content discovery, personalized learning, and machine-assisted teaching and grading. We believe the next generation of teaching and learning should be personalized, accessible, and efficient. With our scale, data, technology, and talent, Coursera and its Data Science team are positioned to make that vision a reality.
We are looking for a Senior Machine Learning Scientist with expertise in fields of search ranking and personalization to join our Data Science team. In this role, you will be responsible for developing and deploying state-of-the-art machine learning algorithms supporting search relevance, ranking and personalization applications. As a senior member of the team, you are expected to partner with the Product team to drive the AI vision for the mentioned applications for Coursera and furthermore, to provide technical mentorship to junior ML scientists in the team.
- Design, build and deploy state-of-the-art ML/AI models to improve search relevance, ranking and personalization experience.
- Leverage large-scale data and ML/AI techniques to improve search relevance and ranking including indexing, query understanding, retrieval and ranking. Provide the user with results that best satisfies their intent and information seeking needs.
- Work closely with Engineering team to establish a vision and support the development of an scalable ML infrastructure
- Partner with Product partner and cross-functional team to understand customer behavior and incorporate the information into advancing your models
- Partner with Product stakeholders to define a long-term AI vision for search relevance, ranking and personalization domains and help the Product stakeholders with the roadmap planning
- Provide technical mentorship to junior ML Scientists in the team.
- A college degree in Computer Science, Information Retrieval, Machine Learning, Mathematics or other related fields
- 4+ years of industrial experience developing large-scale ML/AI models, applications, pipelines and architecture in search ranking and ML/AI personalization supporting search applications.
- 3+ years of demonstrated experience working with product teams and other cross-functional teams.
- Excellent knowledge in search and information retrieval fundamentals including indexing, query understanding, retrieval and ranking
- Strong proficiency in data structures, algorithms and online experimentation.Strong proficiency in at least one modern programming language such as Python, Java, C, C++. Proficiency in SQL.
- Experience with distributed processing architecture and ML/data workflow management platform (Spark, Databricks, Airflow, Kubeflow, etc)
- Ph.D. in Computer Science, Information Retrieval, Machine Learning, Mathematics or other related fields.
- Experience in software system design.
- Experience working with cloud-based solutions, especially AWS.
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