Director ML Platform Engineering

What's the opportunity?

We’re looking for a Director ML Platform Engineering who will bring focus and subject‑matter expertise around designing and implementing machine learning infrastructure and automation tools (MLOps and Dev Ops). 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.

• 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.

• Strong and relevant experience designing and implementing distributed systems and machine learning systems;
• Working with building and maintaining Dev Ops pipeline such as Jenkins, Git Hub Actions;
• Previous experience with MLOps orchestration tools such as Air Flow, Kube Flow, Dagster, Flyte, or Meta Flow;
• In‑depth knowledge of various stages of the machine learning application deployment process;
• Experience with building tools and applications to automate various infrastructure and Dev Ops tasks;
• Proficiency with programming languages such as Python, Bash, or JavaScript;
• Solid understanding of the UNIX operating system;
• Experience 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, Tensor Flow and/or similar.

• 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.

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, scalable, data‑driven solutions that will help communities thrive and drive innovation for our customers across the bank.

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.

• Address: RBC WATERPARK PLACE, 88 QUEENS QUAY W : 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:
• Final date to receive applications:
• Note:
  
  Applications will be accepted until 11:59 PM on the day prior to the Final date to receive applications date above.

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