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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