2027 Capital Markets, Global Equities, AI Engineer (16 Months, Co-op)

RBC is hiring a 2027 Capital Markets, Global Equities, AI Engineer (16 Months, Co-op) in Toronto, Canada. It pays $60k-$100k a year and Level rates it ; you can apply on RBC.

Level's read on this job

Builds AI ●●●● is how Level rates this AI engineer role: the job is building AI systems.
Tools and skills the posting cites include PyTorch, scikit-learn and MLflow.
Level classifies it as an internship.
Level lists 813 other open roles at RBC.
The role was posted within the past week.

AI in this role

AI Engineer Co-op to develop and optimize AI-driven trade execution algorithms and quantitative finance models.

PyTorchscikit-learnMLflowPythonNumpypandasSeabornStreamlitUnix

machine-learningdeep-learningreinforcement-learningquantitative-financedata-science

Job Description

RBC Capital Markets is seeking highly skilled and motivated individuals to join our Algo Research team as AI Engineers. Our team is at the forefront of leveraging artificial intelligence and machine learning to develop innovative trade execution algorithms and advanced analytics solutions. This role presents a unique opportunity to contribute to cutting-edge research and development in quantitative finance, working alongside top-tier professionals in a dynamic and collaborative environment.

We are particularly interested in candidates with strong technical expertise, a passion for data-driven problem-solving, and the ability to apply advanced AI techniques to real-world problems. Experience in finance is not required.

This internship position is 16 months in duration, from May 2027 to August 2028. Students are expected to return to school following the completion of the internship.

What We’re Looking For:

We are seeking candidates who demonstrate the following qualifications and attributes:

Software Engineering & Programming: Expertise in Python, and knowledge of databases, scripting, Unix systems, data structures, and networking.
Applied Machine Learning: Proficiency in ML techniques (e.g. Feature Engineering, Loss Function Design, Deep learning, Reinforcement Learning) and tools (e.g. PyTorch, Scikit-learn, MLflow).
Data Science: Experience working with large datasets to extract insights and create visualizations using libraries like NumPy, Pandas, Seaborn, and Streamlit
Probability & Statistics: Strong understanding of probability concepts and statistical methods.
Communication: Skilled in conveying quantitative concepts to non-technical stakeholders.

Key Responsibilities:

Employ advanced machine learning techniques to address complex trading related problems.
Develop and optimize AI-driven trading algorithms/strategies and incorporate them into client-facing applications.
Collaborate with traders, researchers, and subject matter experts to conceptualize and implement innovative products.
Analyze large datasets to derive actionable insights and create impactful visualizations.
Contribute to a variety of high-impact projects spanning multiple asset classes and trading strategies.

Why Join RBC Capital Markets?

Be part of a forward-thinking team at the forefront of AI-driven innovation in finance.
Collaborate with industry-leading experts on Canada’s largest trade floor.
Gain exposure to real-world applications of artificial intelligence and machine learning in quantitative trading.
Thrive in a culture that values innovation, collaboration, and continuous professional development.

If you are a highly motivated individual with a strong technical background and a desire to contribute to the future of quantitative finance, we invite you to apply for this exciting opportunity.

In order for your application to be considered, please upload your COVER LETTER and RESUME as ONE PDF FILE.

We thank all interested candidates; however, only those selected for an interview will be contacted.

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

Job Skills

Additional Job Details

Address:

ROYAL BANK PLAZA, 200 BAY ST:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

CAPITAL MARKETS

Job Type:

Student/Coop (Fixed Term)

Pay Type:

Salaried

Posted Date:

2026-09-14

Application Deadline:

2026-11-16

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

Pay Range

The expected pay range for this position is:

$60,000.00 - $100,000.00

The pay range provided is for the primary work location referenced in the Additional Job Details section of this job posting. RBC supports pay transparency and we strive to ensure all pay ranges and competitive, fair, and equitable. Your actual pay is determined by a number of factors, including your experience, skills and education.

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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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.

How we rate this

2027 Capital Markets, Global Equities, AI Engineer (16 Months, Co-op) at RBC rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

2027 Capital Markets, Global Equities, AI Engineer (16 Months, Co-op) is an open job at RBC.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $60k-$100k a year.
The role is based in TORONTO, Ontario, Canada.
The job was posted on November 3, 2026.
Seniority: intern.
Applications are handled by RBC. Apply on RBC

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningDeep learningReinforcement learningQuantitative FinanceData SciencePyTorchscikit-learnMLflow

Also common in AI engineer jobs at this level

LLM AI agents AWS Generative AI Azure RAG

Pay

This job starts at: $60k
Typical AI engineer job: $183k

This posting starts 67% below the typical AI engineer job. See AI engineer jobs

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where reinforcement learning was part of your work. What did you do?
Tell me about a project where quantitative finance was part of your work. What did you do?
Tell me about a project where data science was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Machine learning, Deep learning, Reinforcement learning, Quantitative Finance, and Data Science. 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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