Corporate jobs in United States

Job Summary

Directs and leads the operation and delivery of machine learning programs and projects. Manages activities through senior managers and managers and implements corporate and divisional strategic plans and budgets.

Job Description

• What is the opportunity?

  Global Functions Technology (GFT) is part of RBC’s Technology and Operations division. GFT’s impact is far-reaching as we collaborate with partners from across the company to deliver innovative and transformative IT solutions. Our clients represent Risk, Finance, HR, CAO, Audit, Legal, Compliance, Financial Crime, Capital Markets, Personal and Commercial Banking and Wealth Management. We also lead the development of digital tools and platforms to enhance collaboration.

  We’re seeking a Lead Machine Learning Engineer focused on building and scaling data-driven systems that enable advanced analytics, machine learning, and impactful business decisions. You will play a key role in shaping our next-generation trading decisioning and risk management platform, and lead by example in applying sound architectural thinking, engineering rigor, and technical mentorship.

  What will you do?

• Lead by Doing: Design, build, and review scalable data pipelines, analytics platforms, and ML systems. This is a hands-on role with end-to-end ownership, with significant time doing coding.
• Set Technical Direction: Define and promote best practices in data and ML engineering. Evaluate emerging technologies and guide adoption to drive innovation.
• Partner Cross-Functionally: Work closely with data scientists, business leaders, and IT teams to understand needs and translate them into technical solutions.
• Deliver at Scale: Ensure projects are executed with high quality, on time, and aligned with business goals. Proactively identify risks and enforce compliance standards, especially around data governance and security.

• What do you need to succeed?

  Must Have:

• 10+ years of experience in designing and building data-intensive applications with deep understanding of distributed systems
• 3+ years in engineering leadership role
• Deep expertise in modern data and ML engineering tools and languages (e.g., Python, Java/Scala, Spark, Pyspark, Kafka, SQL, Airflow).
• Strong understanding of the ML lifecycle and MLOps practices, including model deployment, monitoring, and CI/CD pipelines.
• Proven experience in cloud platforms like AWS or Azure, with knowledge of scalable architecture patterns.
• Excellent communication skills—able to clearly explain complex technical concepts to both technical and non-technical audiences.
• Bachelor’s degree in computer science, Engineering, or a related field; Master's or PhD preferred.

• Nice to Have:

• Hands-on experience with Snowflake, AWS SageMaker, LLM deployments
• Background in enterprise-level data governance, privacy, and security practices.

Job Skills

Big Data Management, Data Modeling, Data Science, Decision Making, Deep Learning, Machine Learning, Predictive Analytics, Programming Languages, Relationship Building

Additional Job Details

Address:

RBC CENTRE, 155 WELLINGTON ST 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:

2025-06-05

Application Deadline:

2025-06-30

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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