ML software engineer

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

ML software engineer

Overview:
Dynamic Yield by Mastercard is seeking an MLOps Engineer who has 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 an MLOps Engineer, you will have the unique opportunity to play a pivotal role in building and maintaining our machine learning infrastructure and operations. We value MLOps engineers with a diverse skill set, a comprehensive background in both machine learning and DevOps, and a genuine interest in optimizing the deployment, monitoring, and maintenance of ML models beyond standard practices.

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:

Abide by Mastercard’s security policies and practices;

Ensure the confidentiality and integrity of the information being accessed;

Report any suspected information security violation or breach, and

Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.