Senior Machine Learning 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

Senior Machine Learning Engineer

Mastercard is a world leading payments and technology company with the aspiration to help reshape the digital economy so everyone can realize their ambitions. Technology is our product, and we pride ourselves in using the latest technologies to create secure, customer centric experiences.

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. 

Overview

Job Title: Senior ML Engineer

Reporting to the Director of Applied AI and working the with the Applied AI team, the ML Engineer will enable AI impact at scale by building AI-powered applications and managing the MLOps lifecycle.

Responsibilities:
• Participate in team prioritization discussions with Product/Business stakeholders
• Estimate and own delivery tasks (design, dev, test, deployment, configuration, documentation) to meet the business requirements.
• Automate build, operate, and run aspects of software
• Drive code/design/process trade-off discussions within their team when required
• Report status and manage risks within their primary application/service
• Drive integration of services focusing on customer journey and experience
• Perform demos/acceptance discussions in interacting with Product owners
• Develop complete understanding of end-to-end technical architecture and dependency systems.
• Drive adoption of technology standards and opinionated frameworks, and review coding, test, and automation work of team members
• Mentor and guide new and less-experienced team members.
• Identify opportunities to improve an overall process and trim waste.
• Share and seek knowledge within their Guild/Program to drive reuse of patterns/libraries/practices and enhance productivity.
 

Skills & Experience:
• Bachelor’s degree in computer science, Software Engineering, or a related field
• 4+ years of experience in Software Engineering with exposure to Data Engineering or Data Science
• Strong proficiency in programming languages like Python, Java, or Scala.
• Familiarity to basic AI/ML concepts ( model training, serving etc)
• Understands internals of operating systems (Windows, Linux) to write interoperable and performant code.
• Able to perform debugging and troubleshooting to analyze core, heap, thread dumps and remove coding errors.
• Understands and implements standard branching (e.g., Gitflow), peer reviews and CI/CD practices (e.g. Jenkins)
• Has skills in test driven and behavior driven development (TDD and BDD) to build just enough code and collaborate on the desired functionality.
• Understands and implements Application Programming Interface (API) standards and cataloging to drive API/service adoption and commercialization.
• Apply tools (e.g., Sonar, Checkmarx) and techniques to scan and measure code quality and anti-patterns as part of development activity.
• Has skills to collaborate with team and business stakeholders to estimate requirements (e.g., story pointing) and prioritize based on business value.
• Excellent communication and collaboration skills.
• Ability to work independently and as part of a team.
• Familiarity with cloud platforms (AWS, Azure, Databricks) is a plus.


Mastercard is an inclus