Senior Machine Learning Scientist

Job Overview:

We are seeking a Machine Learning Scientist (Recommendations) to join our Discovery Science ML team at Coursera, focusing on creating the next generation of hyper-personalized recommender  systems. The candidate will play an instrumental role in researching and developing state-of-the-art techniques for relevant, personalized, and context-aware recommendations — redefining the learning experience on our platform. In addition to helping build a robust recommendations  system, this role requires keeping abreast of emerging trends and innovations in machine learning, information retrieval,  and online education.

Responsibilities:

• Design, develop, deploy, and maintain advanced recommendations ranking models, leveraging machine learning techniques such as two tower models, natural language processing (NLP), label collection, learning-to-rank, user behavior analysis, & LLMs

• Collaborate with cross-functional teams to align research goals with business needs and ensure successful deployment of innovative solutions into production.

• Build and manage large-scale datasets, including corpora, relevance labels, and user interactions, utilizing tools and techniques for data collection, cleaning, and preprocessing.

• Conduct thorough evaluations of recommendations  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, recommender systems, search science, 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.

Basic Qualifications:

• PhD or Master's degree in Computer Science, Information Retrieval, or closely related fields.

• Demonstrated experience in developing advanced recommendations  models, 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 SIGIR, EMNLP, WWW, CIKM, or similar venues.

Preferred Qualifications:

• Proficiency in programming languages and deep learning frameworks such as Python, TensorFlow, or PyTorch.

• Experience in working with large-scale 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 and recommendations domain.

• Experience with MLOps, ML engineering

• Experience collaborating with cross-functional teams and excellent communication abilities.

• Passion for driving impact in the field of online education through innovative ML and recommendations techniques.

• Familiarity with Coursera's platform and course offerings, as well as active participation in wider AI and Machine Learning communities, is a plus.

• Familiarity with data science concepts, including the ability to design, implement, and analyze A/B tests in an online environment to optimize product performance and user experience.

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

• Unsupervised Learning, Recommenders, Reinforcement Learning

• Recommender Systems: Evaluation and Metrics  

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