Time since we first saw it
Day 17
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 17 days agoPay Ranges Vancouver, Canada: $111,000 - $160,000 CADRead the full posting
Support machine learning models that detect cyber-attacks and fraud
Create data pipelines and feature engineering workflows for model development
Process and analyze large-scale datasets to improve model inputs
Strengthen monitoring, observability, and drift detection in production
Apply automation and MLOps practices to improve reliability and scalability
Support machine learning models that help detect cyber-attacks, fraud and improve decision intelligence.
Create data pipelines and feature engineering workflows that enable model development and evaluation.
Process and analyze large-scale datasets to uncover insights and improve model inputs.
Strengthen monitoring, observability, and drift detection capabilities across production environments.
Apply automation and MLOps practices to improve reliability, efficiency, and scalability.
Role As a Senior AI Engineer, you will: • Support machine learning models that help detect cyber-attacks, fraud and improve decision intelligence. • Create data pipelines and feature engineering workflows that enable model development and evaluation. • Process and analyze large-scale datasets to uncover insights and improve model inputs. • Strengthen monitoring, observability, and drift detection capabilities across production environments. • Apply automation and MLOps practices to improve reliability, efficiency, and scalability. • Develop AI-powered solutions that address engineering challenges and streamline operational processes. -Partner with Data Scientists, Engineers, and Product teams to bring new capabilities into production. • Contribute ideas that improve model performance, operational visibility, and team productivity. Required Qualifications • Master’s degree with relevant experience, or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field; equivalent practical experience will also be considered. • Proficiency in Python, PySpark, SQL, and distributed data processing. • Hands-on experience with feature engineering, large-scale data processing, and analytics. • Hands-on experience with Databricks, Airflow, Hadoop, Linux/Unix, cloud-native technologies • Understanding of machine learning and deep learning techniques. • Understanding of model deployment, evaluation, monitoring, and optimization. • Knowledge of MLOps concepts including testing, automation, CI/CD, and version control. • Ability to communicate technical concepts and collaborate across teams. Preferred Qualifications • Fraud, cybersecurity, payments, or risk management domains. • Experience with Generative AI, LLMs, RAG, or agentic AI applications. • Familiar with AI-assisted development tools such as GitHub Copilot, or Claude Code. • Experience working with cloud-based data and AI environments.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 17
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.
Role As a Senior AI Engineer, you will: • Support machine learning models that help detect cyber-attacks, fraud and improve decision intelligence. • Create data pipelines and feature engineering workflows that enable model development and evaluation. • Process and analyze large-scale datasets to uncover insights and improve model inputs. • Strengthen monitoring, observability, and drift detection capabilities across production environments. • Apply automation and MLOps practices to improve reliability, efficiency, and scalability. • Develop AI-powered solutions that address engineering challenges and streamline operational processes. -Partner with Data Scientists, Engineers, and Product teams to bring new capabilities into production. • Contribute ideas that improve model performance, operational visibility, and team productivity. Required Qualifications • Master’s degree with relevant experience, or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field; equivalent practical experience will also be considered. • Proficiency in Python, PySpark, SQL, and distributed data processing. • Hands-on experience with feature engineering, large-scale data processing, and analytics. • Hands-on experience with Databricks, Airflow, Hadoop, Linux/Unix, cloud-native technologies • Understanding of machine learning and deep learning techniques. • Understanding of model deployment, evaluation, monitoring, and optimization. • Knowledge of MLOps concepts including testing, automation, CI/CD, and version control. • Ability to communicate technical concepts and collaborate across teams. Preferred Qualifications • Fraud, cybersecurity, payments, or risk management domains. • Experience with Generative AI, LLMs, RAG, or agentic AI applications. • Familiar with AI-assisted development tools such as GitHub Copilot, or Claude Code. • Experience working with cloud-based data and AI environments.
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Already applied? Track this application
Yes. We’ve followed one other Senior AI Engineer, Big Data & AI Solutions job there since August 2026. It is still up.
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
Senior AI Engineer, Big Data & AI SolutionsWho 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: $111,000 - $160,000 CADSelected passages from the saved posting. Check the full description for conditions and exceptions.
Pay Ranges Vancouver, Canada: $111,000 - $160,000 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.