Full Stack Machine Learning Scientist

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 124 million registered learners. 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. As a B Corp, we're committed to driving positive social and environmental impact while delivering high-quality learning experiences. Our platform is used by institutions worldwide to upskill and reskill employees, citizens, and students across industries, including data science, technology, and business.

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.

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 82 million registered learners as of March 31, 2021. Coursera partners with over 200 leading university and industry partners to offer a broad catalog of content and credentials, including Guided Projects, courses, Specializations, certificates, and bachelor’s and master’s degrees. More than 6,000 institutions have used Coursera to upskill and reskill their employees, citizens, and students, including in high-demand fields such as data science, technology, and business. Coursera became a B Corp in February 2021.

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:

• Partner with cross functional stakeholders to define a long-term vision for scaling ML/AI applications in production and help teams with their roadmap plannings
• Work very closely with ML scientists to find and solve engineering pain-points by building scalable, general-use platforms
• Automate ML workflows to enhance productivity across training, evaluation, testing, and results generation
• Build scalable and reliable infrastructure and pipelines for data/feature processing and storage and also scalable training and evaluation infrastructure and pipelines to accelerate model development
• Work very closely with ML scientists and help them with model deployment in the production systems
• Provide technical mentorship to junior ML Engineers and act as a technical leader for the ML engineering domain

Basic Qualifications:

• Experience with containerization such as Docker and Kubernates
• Highly skilled with Java development, Python and SQL/MySQL.
• Highly skilled with distributed processing architecture and ML/data workflow management platform (Spark, Databricks, Airflow, Kubeflow, MLflow etc)
• Solid understanding and experience in system design of ML systems (design pattern, OOD, architecture, modules, interfaces, etc)
• Highly skilled with strong proficiency in ML ops with experience in building large-scale ML applications, services, pipelines and architecture

Preferred Qualifications:

• Knowledge in c++ or c# would be also preferred.
• Experience with CI/CD pipelines, integrated tests and test-driven development
• Solid understanding in machine learning theory and practice, and experience using machine learning tools (Scikit-Learn, TensorFlow, Weka etc.)
• Solid understanding and experience working with cloud-based solutions, especially AWS
• Experience with microservice architectures such as RESTful web-services

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

• Computer Vision for Engineering and Science Specialization
• Natural Language Processing Specialization
• Machine Learning Engineering for Production (MLOps) Specialization

Compensation:

Our job titles may span more than one career level. The starting base pay for this role is between $118,000 and $219,000. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs, and location. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, and benefits.

Coursera is an Equal Employment Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, age, marital status, national origin, protected veteran status, disability, or any other legally protected class.

If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, please contact us at [email protected].

For California Candidates, please review our CCPA Applicant Notice here.

For our Global Candidates, please review our GDPR Recruitment Notice here.