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Added 14 mins ago
Manager, Software Engineering
AltaML
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Full-time
We overpay for the right people. We'd rather pay a premium for an engineer who embodies this and multiplies the team than save money on someone who doesn't.
Added 14 mins ago
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7shifts
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RBC

Lead ML Platform Engineer

Calgary, AB, Canada

Job type: Full-time
Apply by: Oct 15, 2026
Experience: 5+ years of experience designing and implementing distributed systems and Machine Learning systems;
Posting language: English
Posted: Sep 28, 2026

Apply About employer

Applications open in a new tab.

Original job description

Job Description

What's the opportunity?

We’re looking for an experienced Machine Learning Platform Engineer who will bring focus and subject-matter expertise around designing and implementing machine learning infrastructure and automation tools (MLOps and DevOps). This is a unique opportunity to grow in the world of machine learning infrastructure and work with a team of passionate individuals committed to the mission of bringing ML to enterprise.

At RBC Borealis, you’ll be joining a team that works directly with leading researchers in machine learning, has access to rich and massive datasets, and offers the computational resources to support ongoing development in areas such as reinforcement learning, unsupervised learning and computer vision. You can find out more about our research areas at rbcborealis.com.

Your responsibilities include:

Designing, building, and optimizing machine learning deployment tools and automation systems that operate the business’s data and ML applications;
Designing and implementing best practices and standards for data and machine learning pipelines across the organization;
Collaborating with engineers, and machine learning researchers to automate code analysis, build, integration and deployment of ML applications;
Supporting applications and projects with infrastructure design decision, and monitoring solution;
Building highly scalable, resilient cloud and on-premise systems for hosting machine learning systems using state-of-the-art technologies.

You're our ideal candidate if you have:

5+ years of experience designing and implementing distributed systems and Machine Learning systems;
Working with building and maintaining DevOps pipeline such as Jenkins, GitHub actions;
Previous experience with MLOps orchestration tools such as AirFlow, KubeFlow, Dagster, Flyte, or MetaFlow;
In-depth knowledge of various stages of the machine learning application deployment process;
Experience with building tools and applications to automate various infrastructure and DevOps tasks;
Proficiency with programming languages such as Python, Bash, or JavaScript;
Solid understanding of the UNIX operating system;
Implementing monitoring solutions to identify system bottlenecks and production issues;
Knowledge of professional software engineering best practices for the full software development life cycle, including testing methods, coding standards, code reviews and source control management;
Hands-on experience building and deploying hybrid environments on-prem and major cloud environments, such as AWS and Azure;
Familiarity with machine learning frameworks such as PyTorch, TensorFlow and/or similar.

What's in it for you?

Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;
A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;
Leaders who support your development through coaching and managing opportunities;
Ability to make a difference and lasting impact from a local-to-global scale.

About RBC Borealis

RBC Borealis is the driving force behind Royal Bank of Canada’s AI and data innovation. As part of Canada’s largest financial institution, we bring together a team of architects, engineers, scientists, and product experts on a mission to revolutionize finance through world-class research, solutions, and a resilient data platform. With locations across Toronto, Waterloo, Montreal, Calgary, and Vancouver, we’re at the forefront of AI research and platform development. With a focus on cutting-edge research in areas like time series forecasting, causal machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable, data-driven solutions that will help communities thrive and drive innovation for our customers across the bank.

Inclusion and Equal Opportunity Employment

RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.

#TECHPJ

#Ll-POST

Job Skills

Apache Airflow, Apache Spark, Application Development, Application Maintenance, Applications Architecture, Applications Programming, Cloud Computing, Code Development, Detail-Oriented, Group Problem Solving, Jupyter Notebooks, Python (Programming Language), Red Hat OpenShift, Software Development Life Cycle (SDLC) Methodologies, Technical Design Documentation, Unit Testing

Additional Job Details

Address:

335 8 AVE SW:CALGARY

City:

Calgary

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-09-10

Application Deadline:

2026-10-15

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

Join our Talent Community

Stay in-the-know about great career opportunities at RBC. Sign up and get customized info on our latest jobs, career tips and Recruitment events that matter to you.

Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

Apply About employer

More about this job

Responsibilities

You will design, build, and optimize machine learning deployment tools and automation systems while establishing best practices for data and ML pipelines. Additionally, you will collaborate with researchers to automate code analysis and build scalable, resilient infrastructure for ML applications.

Requirements

The ideal candidate possesses 5+ years of experience in distributed systems and machine learning infrastructure. Proficiency in Python, DevOps pipelines, MLOps orchestration tools, and cloud environments like AWS or Azure is required.

Skills

Machine learning infrastructure
MLOps
DevOps
Distributed systems
Jenkins
GitHub actions
AirFlow
KubeFlow
Python
Bash
JavaScript
UNIX
AWS
Azure
PyTorch
TensorFlow

Benefits

Bonuses
Flexible benefits
Competitive compensation
Commissions
Stock options

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
MLOps
DevOps
Infrastructure
Automation
Distributed Systems
Jenkins
GitHub Actions
AirFlow
KubeFlow
Dagster
Flyte
MetaFlow
Python
Bash
JavaScript
UNIX
AWS
Azure
PyTorch
TensorFlow
Cloud Computing
Data Engineering
Reinforcement Learning
Computer Vision
Time Series Forecasting
Causal Machine Learning
Responsible AI
Hybrid Environments

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