Mistral AISingapore3h ago
RBCPosted 1mo ago
Senior Machine Learning Software Engineer at RBC scores 85 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
Job Description
What's the opportunity?
At RBC Borealis, you’ll be joining a team of leading researchers and software engineering specializing in machine learning. You will have access to rich and massive datasets, and to computational resources to support novel product development touching machine learning areas such as generative AI, natural language processing, and time series analysis.
We’re looking for an enthusiastic software developer who’s excited by the opportunity of working on challenging problems at the intersection of machine learning and the financial services industry. As a Senior Machine Learning Software Engineer, you’ll be responsible for owning and delivering a project end to end – everything from data pre-processing and exploration, to building and scaling ML algorithms and pipelines, to deployment and monitoring of production systems. 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 cutting-edge machine learning R&D.
Your responsibilities include:
- Lead development of machine learning-based software solutions throughout the research and product development lifecycle;
- To play a key role in the design and development of Borealis’ machine learning products;
- To partner with RBC Borealis’s research and product teams to ensure the seamless delivery of these products;
- To apply engineering and data best practices to build robust and scalable large-scale machine learning software systems;
- To support projects with thorough documentation, design decisions, and technical advisory.
You're our ideal candidate if you have:
- A degree in Computer Science, Software Engineering, or equivalent field;
- 7+ years of experience as a software engineer;
- Experience building modular and robust software systems in Python or similar language;
- 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;
- Experience working across the entire ML research and product lifecycle from prototyping to production is a plus;
- Experience building microservices, data pipelines and using relational and non-relational databases is a plus;
- Experience working with data science tooling and deep learning frameworks is a plus;
- Experience with DevOps engineering (CI/CD pipelines, observability, containers etc) is a plus.
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 the AI Group:
RBC's AI Group is the AI accelerator for RBC, with a focus on driving the shift from early-stage AI projects to scaled, client outcomes that amplify the impact of RBC's people. In addition to helping scale the biggest AI opportunities at RBC, the AI Group is responsible for advancing research into emerging use cases across generative and agentic AI, while maintaining expertise in security, responsible AI and regulatory expectations. The Business Enablement function within the AI Group partners with LOBs and Functions to set AI ambition, originate transformation opportunities, and frame programs for delivery — ensuring RBC remains at the frontier of AI-enabled value creation.
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.
#LI-POST
#TECHPJ
Job Skills
Big Data Analytics, Client Counseling, Coaching Others, Critical Thinking, Decision Making, Industry Knowledge, Machine Learning (ML), Software Engineering, Software Product DesignAdditional Job Details
Address:
777 BAY ST, TH 27:TORONTOCity:
TorontoCountry:
CanadaWork hours/week:
37.5Employment Type:
Full timePlatform:
TECHNOLOGY AND OPERATIONSJob Type:
RegularPay Type:
SalariedPosted Date:
2026-07-03Application Deadline:
2026-09-30Note: 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.
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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.
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Skills and AI tools this role asks for
Questions you could be asked
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- How do you think about the risk of an AI system in this kind of role failing silently?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: Nlp and AI Safety. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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