Staff Machine Learning Scientist at Coursera

Job Overview:
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 Staff Machine Learning Scientist with expertise in fields of recommender systems, 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 recommendation, 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.
Responsibilities:

Develop and deploy state-of-the-art recommendation, search ranking and personalization ML/AI models 
Use statistical and optimization techniques to build high performing recommendation, search ranking and personalization models
Partner with UX research, UX design and Product teams to understand customer behavior and incorporate the information into advancing your models
Partner with Product stakeholders to define a long-term AI vision for the recommendation, search ranking and personalization domains and help the Product stakeholders with the roadmap planning
Partner with Engineering team to establish a vision and support the development of an scalable ML infrastructure 
Provide technical mentorship to junior ML Scientists and act as a technical leader for recommendation, search ranking and personalization domains

Basic Qualifications:

A college degree in Computer Science, Software Engineering, Mathematics or other related fields
5-7 + years of industrial experience developing advanced ML/AI models in one or more of the following areas:  recommender systems, search ranking, and personalization applications
3+ years of demonstrated experience independently balancing priorities and managing projects across multiple stakeholders
Strong proficiency in machine learning and deep learning technologies particularly with experience building large-scale ML applications, pipelines, model architecture design, training in recommendation and ranking
Strong Proficiency in data structures, algorithms and online experimentation. Proficiency in SQL and at least one programming language such as Python or Java. 
Experience with distributed processing architecture and ML/data workflow management platform (Spark, Databricks, Airflow, Kubeflow, etc)
Excellent communicator - able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion

Preferred Qualifications:

Ph.D. in Computer Science, Software Engineering, Mathematics or other related fields.
Experience in software system design.
Experience working with cloud-based solutions, especially AWS. 
Knowledge in c++ or c# would be also preferred.

If this opportunity interests you, you might like these courses on Coursera:

Deep Learning Specialization
Machine Learning Engineering for Production (MLOps) Specialization

 
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