Join Coursera's Machine Learning team, where you will play a pivotal role in revolutionizing education through advanced AI technologies such as natural language processing, computer vision, and generative models. Your work will help drive content discovery, personalized learning, machine translation, skill tagging, and machine-assisted teaching and grading. We are looking for a talented Machine Learning Engineer to build scalable infrastructure, automate ML workflows, and collaborate with cross-functional teams to bring our vision of a next-generation education experience to life.

Key Responsibilities

• Collaborate closely with ML scientists to deploy models in production systems and address engineering challenges by developing scalable, general-use platforms.
• Design and implement reliable infrastructure and pipelines for data processing, feature storage, and model training and evaluation.
• Automate ML workflows to boost productivity in training, evaluation, testing, and results generation.
• Partner with stakeholders to define and execute a long-term vision for scaling ML/AI applications and assist in roadmap planning.
• Provide technical mentorship to junior engineers and lead technical initiatives in the ML engineering domain.

Basic Qualifications

• Bachelor’s degree in Computer Science or a related field, with at least 4 years of industry experience in machine learning.
• Proficiency in Java, Python, and SQL/MySQL.
• Extensive experience in ML Ops, including building large-scale ML applications, services, and pipelines.
• Strong understanding of system design for ML systems, including design patterns, OOD, architecture, and interfaces.
• Experience with distributed processing architectures and ML/data workflow management platforms (e.g., Spark, Databricks, Airflow, Kubeflow, MLflow).
• Familiarity with containerization technologies such as Docker and Kubernetes.

Preferred Qualifications

• Master’s or Ph.D. in Computer Science or a related field with 4 years of industry experience in machine learning.
• Deep understanding of machine learning theory and practice, with experience in tools like Scikit-Learn, TensorFlow, and PyTorch.
• Experience with cloud-based solutions, especially AWS.
• Knowledge of C++ or C#.
• Familiarity with CI/CD pipelines, integrated tests, and test-driven development.
• Experience with microservice architectures, including RESTful web services.
• Contributions to the machine learning community through publications in top-tier conferences or involvement in open-source communities like Hugging Face.

Why Coursera?

1. Impact. Join a mission-driven company transforming lives through accessible education.
2. Diversity. Be part of a globally diverse team and contribute to a culture of inclusion.
3. Innovation. Work with cutting-edge technologies in AI and machine learning.
4. Flexibility. Enjoy a remote-first work environment with a virtual interview and onboarding process.

Interested?

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

Coursera is an Equal Employment Opportunity Employer. We consider 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 require accommodation due to a disability, please contact us at [email protected].