Our Purpose
We work to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.
Title and Summary
Software Engineer
Overview:
Dynamic Yield by Mastercard is seeking a back-end engineer with a deep passion for machine learning, operations, and technology, combined with a strong drive to implement scalable and efficient solutions. We foster a professional environment where experienced engineers collaborate and contribute to the team's success while continuously enhancing their own skills. As a back-end Engineer, you will have the unique opportunity to play a pivotal role in building and maintaining our machine learning infrastructure and operations.
Role:
* Design, implement, and maintain scalable ML infrastructure for model training, deployment, and monitoring
* Ownership of the technical architecture for new ML operations features and enhancements
* Lead the development and optimization of ML pipelines, ensuring robust and efficient workflows
* Stay updated and lead technological advances in ML operations and infrastructure
* Collaborate with data scientists and engineers to integrate ML models into production systems
All about You/Experience:
* At least 4 years of solid experience in Backend Engineering
* At least 3 years of experience with cloud platforms like AWS, GCP, or Azure
* Minimum 2 years of solid experience with containerization and orchestration tools like Docker and Kubernetes
* Excellent verbal and written communication skills in English
* A degree in Computer Science, Data Science, or a related discipline, or relevant industry experience
* Self-taught practitioners are always welcome
* At least 2 years of experience with continuous integration/continuous deployment (CI/CD) tools and practices
* Hands-on experience building and managing data pipelines and workflows
* Familiarity with SQL & NoSQL databases (e.g., MySQL, Redis)
* Experience in Python advantage
* Experience with ML frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
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Abide by Mastercard’s security policies and practices;
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Ensure the confidentiality and integrity of the information being accessed;
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Report any suspected information security violation or breach, and
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Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
Top Skills
What We Do
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Why Work With Us
We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.