About Coursera
Coursera was launched in 2012 by Andrew Ng and Daphne Koller with a mission to provide universal access to world-class learning. Today, it is one of the largest online learning platforms in the world, with 197 million registered learners as of December 31, 2025.
Coursera partners with over 375 leading university and industry partners to offer a broad catalog of content and credentials, including courses, Specializations, Professional Certificates, and degrees. Coursera’s platform innovations — including generative AI-powered features like Coach, Role Play, and Course Builder, and role-based solutions like Skills Tracks — enable instructors, partners, and companies to deliver scalable, personalized, and verified learning.
Institutions worldwide rely on Coursera to upskill and reskill their employees, students, and citizens in high-demand fields such as GenAI, data science, technology, and business, while learners globally turn to Coursera to master the skills they need to advance their careers. Coursera is a Delaware public benefit corporation and a B Corp
Why Join Us
At Coursera, we’re looking for inventors, innovators, and lifelong learners ready to shape the future of education. You’ll help build global programs and tools that power online learning for millions turning bold ideas into real impact. People who thrive here are customer-first builders who move fast, simplify ruthlessly, and iterate relentlessly on the metrics that matter.
We’re a globally distributed team and let you choose the best way you work, whether it's from home, a Coursera hub, or a co-working space near you. Our virtual hiring and onboarding make it easy to join us and start making an impact from anywhere. If you’re ready to make a global impact, scale unique products exclusive to Coursera, and expand your career horizons, apply below.
Job Overview:
At Coursera, our Machine Learning team plays a crucial role in shaping the future of education through cutting-edge AI technologies such as natural language processing, computer vision, and generative models. We are dedicated to defining, developing, and launching models that drive content discovery, personalized learning, machine translation, skill tagging, and machine-assisted teaching and grading. Our vision is centered on creating a next-generation education experience that is personalized, accessible, and efficient. Leveraging our scale, extensive data, advanced technology, and talented team, Coursera is poised to transform this vision into reality.
Responsibilities:
- Work very closely with ML scientists and help them with model deployment in the production systems
- Work very closely with ML scientists to find and solve engineering pain-points by building scalable, general-use platforms
- 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
- Automate ML workflows to enhance productivity across training, evaluation, testing, and results generation
- 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
Basic Qualifications:
- BS in Computer Science, or related area with 3 Years minimum Machine Learning Scientist or Engineer industry experience
- Highly skilled with Java development, Python and SQL/MySQL.
- Highly skilled with proficiency in ML ops with experience in building large-scale ML applications, services, pipelines and architecture
- Solid understanding and experience in system design of ML systems (design pattern, OOD, architecture, modules, interfaces, etc)
- Highly skilled with distributed processing architecture and ML/data workflow management platform (Spark, Databricks, Airflow, Kubeflow, MLflow etc)
- Experience with containerization such as Docker and Kubernates
Preferred Qualifications:
- MS in Computer Science, or related area with 1 Years minimum Machine Learning Engineer industry experience or Ph.D in in Computer Science, or related area
- Understanding in machine learning theory and practice, and experience using machine learning tools (Scikit-Learn, TensorFlow, PyTorch etc.)
- Understanding and experience working with cloud-based solutions, especially AWS, Databricks
- Experience with CI/CD pipelines, integrated tests and test-driven development
- Experience with microservice architectures such as RESTful web-services
If this opportunity interests you, you might like these courses on Coursera:
- Machine Learning Engineering for Production (MLOps) Specialization
- Computer Vision for Engineering and Science Specialization
- Natural Language Processing Specialization
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Coursera is an Equal Opportunity Employer committed to building a welcoming and inclusive workplace. We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request at [email protected]. Learn more in our CCPA Applicant Notice and GDPR Recruitment Notice.
To protect against recruitment fraud, please note that Coursera recruiters will only communicate with candidates using official coursera.org email addresses. We do not conduct interviews or negotiate offers via personal or non-coursera.org accounts.
