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 136 million registered learners as of September 30, 2023.
Coursera partners with over 300 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.
Join us in our mission to create a world where anyone, anywhere can transform their life through access to education. We're seeking talented individuals who share our passion and drive to revolutionize the way the world learns.
We at Coursera are committed to building a globally diverse team and are thrilled to extend employment opportunities to individuals in any country where we have a legal entity. We require candidates to possess eligible working rights and have a compatible timezone overlap with their team to facilitate seamless collaboration. As a remote-first company, our interviews and onboarding are entirely virtual, providing a smooth and efficient experience for our candidates.
Job Overview:
At Coursera, our Machine Learning team is helping to build the future of education through AI such as the natural language process, computer vision, or generative models. We define, develop, and launch the models that power content discovery, personalized learning, machine translation, skill tagging, 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 machine learning team are positioned to make that vision a reality.
Responsibilities:
- Prototyping and developing state-of-the-art machine learning algorithms
- Drive Proof of Concepts (PoC) to explore high impact ML opportunities
- Responsible for ML model deployment, model QA, ML maintenance/monitoring, and the optimization of model runtime performance and scalability in production.
- Work with Product and Business stakeholders to understand customer needs and translate them into ML problems.
- Works with Data Engineering and Product Engineering teams to ensure we have the right data, tools and infrastructures in place to deploy ML models in production.
- Set up project priorities, manage projects deadlines, and ensure projects deliverables
Basic Qualifications:
- MS or Ph.D in in Computer Science, or related area with 3 Years minimum Machine Learning Scientist or Engineer industry experience
- Experience with Python, Java, SQL
- Knowledge in machine learning, computer vision, natural language processing, etc.
- Experience with at least one deep learning framework (e.g., TensorFlow, PyTorch, Caffe, MxNET, etc)
- Experience deploying ML services and applications to at least one major cloud platform (AWS).
Preferred Qualifications:
- Experience with MLOps
- Experience with CI/CD/CT pipelines, integrated tests, and microservice architectures such as RESTful web-services
- Experience with containerization such as Docker and Kubernates
- Able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion
- Experience with contributing machine learning community by publishing papers in the top tier conferences such as CVPR, ICCV, ACL, EMNLP, KDD, ICML, NeruIPS, etc
If this opportunity interests you, you might like these courses on Coursera:
#LI-CP1