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Senior AI Engineer, Big Data & AI Solutions

Reads like an ML Engineer role: training models and running them in production.

Vancouver, British Columbia, Canada

Live, first seen by us 17 days ago
Pay
CAD 111,000–160,000/yearAnnual period assumed — pay source
Pay Ranges Vancouver, Canada: $111,000 - $160,000 CAD
Read the full posting
Work setting
Not stated
Employment
Not stated

What you’ll work on

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

From the employer’s posting
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.
Education & alternatives
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.
Apply at Mastercard

Posting record

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Status in our records
Live
First seen by us
Oct 28, 202617 days ago
Recorded sightings
21
Last seen by us
Nov 14, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

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.

Mastercard is hiring

70 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
  • 9% of open jobs were reposted
Hiring record

See how this role fits your experience

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.

  • Python
  • SQL
  • Databricks
  • Hadoop
  • Airflow
  • PySpark
Where the posting names them
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.

Your next step

Complete your application on mastercard.wd1.myworkdayjobs.com. The employer’s form will show what is required.

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Has Mastercard posted this job before?

Yes. We’ve followed one other Senior AI Engineer, Big Data & AI Solutions job there since August 2026. It is still up.

  1. O FallonStill up after 92 days, first seen Aug 14
  2. This jobUp 18 days so far, first seen Oct 28

About Mastercard

People
About 39,800 in 2025, up 13% from the year before.Annual report (SEC Form 10-K)
Company
Listed as MA.
H-1B visas
36 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 612, the most 1,081, and the latest week had 1,068.
August 17Last week

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.

About the role

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.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

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.

Job description

View original posting ↗

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 Solutions

Who is Mastercard?

Mastercard is a global technology company in the payments industry. Our mission is 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. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

Overview
The Security Solutions Data Science team develops AI and machine learning capabilities that help protect the global payments ecosystem from fraud and cyber threats. Supporting Mastercard's Safety Net product, the team creates and enhances models that analyze billions of transactions and identify suspicious activity in real time.

As a Senior AI Engineer, you will work at the intersection of AI engineering and big data engineering, helping improve the models, data assets, and operational processes that power fraud detection. You will collaborate closely with Data Scientists and Engineers to strengthen feature engineering, advance model monitoring capabilities, and deliver AI-driven solutions that improve performance and efficiency. 

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.

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.

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.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program.

Pay Ranges

Vancouver, Canada: $111,000 - $160,000 CAD

Source details

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Pay
Pay Ranges Vancouver, Canada: $111,000 - $160,000 CAD
Location & working pattern

Vancouver, British Columbia, Canada

Working pattern and location restrictions need checking in the full posting.

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