Lead DevOps Engineer (ML Platform)

Key Skills

Aartificial intelligence, Big Data Technology, Data Analytics, Design, DevOps, Leadership Skill, Machine learning techniques, PyTorch, TensorFlow, Unix Operating system

Job Description

We’re looking for an experienced Lead DevOps Engineer (ML Platform) 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 working experience with building and maintaining DevOps pipeline such as Jenkins, GitHub actions;

• Strong and relevant experience designing and implementing distributed systems and Machine Learning systems;

• 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.

Job Skills

Big Data Analytics, Critical Thinking, Decision Making, Industry Knowledge, Machine Learning, Results-Oriented, Software Engineering, Software Product Design

Additional Job Details

Address:

777 BAY ST, TH 27:TORONTO

City:

TORONTO

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2025-02-25

Application Deadline:

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

Inclusion and Equal Opportunity Employment

At 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.

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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.