Time since we first saw it
Day 45
Similar jobs usually come down between day 8 and day 76.
At Mastercard, jobs usually come down by about day 25.
From 5,517 similar postings that came down, and 270 of Mastercard’s. Coming down is not always a hire.
Reads like an ML Engineer role: training models and running them in production.
Vancouver, British Columbia, Canada
Live, first seen by us 45 days agoPay Ranges Vancouver, Canada: $127,000 - $203,000 CADRead the full posting
Design and build data pipelines that automate repetitive data science and engineering tasks
Integrate data from various sources into cohesive datasets for analysis and modeling
Work with data scientists to find optimization opportunities in the modeling pipeline
Partner with software engineering teams to deploy and validate production artifacts
Design and develop data pipelines to automate repetitive tasks within data science and data engineering.
Oversee the integration and management of data from various sources and storage systems, establishing processes and pipelines to produce cohesive datasets for analysis and modeling.
Lead collaboration with data scientists to understand the existing modeling pipeline and identify optimization opportunities.
Partner with software engineering teams to deploy and validate production artifacts.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 45
Similar jobs usually come down between day 8 and day 76.
At Mastercard, jobs usually come down by about day 25.
From 5,517 similar postings that came down, and 270 of Mastercard’s. Coming down is not always a hire.
70 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
As a Lead AI Engineer, you will: • Lead collaboration with data scientists to understand the existing modeling pipeline and identify optimization opportunities. • Oversee the integration and management of data from various sources and storage systems, establishing processes and pipelines to produce cohesive datasets for analysis and modeling. • Design and develop data pipelines to automate repetitive tasks within data science and data engineering. • Demonstrated experience leading cross-functional teams or working across different teams to solve complex problems. • Partner with software engineering teams to deploy and validate production artifacts. • Identify patterns and innovative solutions in existing spaces, consistently seeking opportunities to simplify, automate tasks, and build reusable components for multiple use cases and teams. • Create data products that are well-modeled, thoroughly documented, and easy to understand and maintain. • Comfortable leading projects in environments with undefined or loose requirements. • Mentor junior AI engineers All About You • Good knowledge of Linux / Bash environment • Experience in the following platforms: Python, Pyspark, Airflow, CI/CD, JIRA, Hadoop, SQL, Databricks • Familiar with agile & agentic engineering best practices • Good communication skills • Highly skilled problem solver • Exhibits a high degree of initiative Nice to have: • Graduate degree in CS, Data Science, Machine Learning, AI or a related STEM field • Data Engineering Experience • Experience with Java • Experience with Jenkins • Experience in with data engineering on petabyte scale data • Understands and implements methods to evaluate own work and others for error • Loves working with error-prone, messy, disparate, unstructured data
All About You • Good knowledge of Linux / Bash environment • Experience in the following platforms: Python, Pyspark, Airflow, CI/CD, JIRA, Hadoop, SQL, Databricks • Familiar with agile & agentic engineering best practices • Good communication skills • Highly skilled problem solver • Exhibits a high degree of initiative Nice to have: • Graduate degree in CS, Data Science, Machine Learning, AI or a related STEM field • Data Engineering Experience • Experience with Java • Experience with Jenkins • Experience in with data engineering on petabyte scale data • Understands and implements methods to evaluate own work and others for error • Loves working with error-prone, messy, disparate, unstructured data Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build 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.
Title and Summary
Lead AI Engineer (AI & Data Strategy)Who is Mastercard?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.
Pay Ranges
Vancouver, Canada: $127,000 - $203,000 CADSelected passages from the saved posting. Check the full description for conditions and exceptions.
Pay Ranges Vancouver, Canada: $127,000 - $203,000 CAD
Vancouver, British Columbia, Canada
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.