Staff Data/ML Engineer

Key Skills

Aartificial intelligence, AWS, Data Engineering, Design, DevOps, Effective communication skills, Large Language Models - LLMs, Machine learning techniques, MLOps tools, Scala Programming, Snowflake, SPARK Programming

Job Description

What is the opportunity?

As a Staff Data/ML Engineer in RBC Borealis Lumina Enablement and Deployment Services (LEADS) organization, you will shape and deliver innovative data and AI solutions on the Lumina platform. In this role, you will partner closely with various PB & CB business and technology teams to design scalable data products, optimize ML workflows, and drive impactful insights. You’ll play a key role in advancing enterprise adoption of Lumina by enabling self-service data and accelerating AI use cases. This is an opportunity to influence strategy while building cutting-edge solutions at scale.

What will you do?

• Design and implement scalable data and AI solutions on the Lumina platform

• Architect and optimize data pipelines and ML workflows to ensure reliability, performance, and cost efficiency

• Develop and curate domain-specific data assets that power advanced analytics and AI use cases across PB & CB

• Implement and operationalize agentic AI workflows to automate decision-making, insights generation, and business process

• Enable self-service data and ML capabilities by building reusable frameworks, tools, and APIs

• Ensure data governance, quality, and security compliance within all solutions delivered

• Drive continuous improvement and innovation by evaluating emerging data and AI technologies for enterprise adoption

What do you need to succeed?

Must have:

• Bachelor’s degree in software engineering, computer science, or a related field

• 5+ years of experience in data/ML engineering or software development roles

• Strong programming skills in Python, Java, or Scala, with expertise in design patterns, testing, and code quality best practices

• Expertise in data engineering with advanced SQL and distributed data processing frameworks (i.e. Spark)

• Ability to design and optimize large-scale, cloud-native data pipelines on platforms such as OCP, AWS, or Azure

• Experience developing production-grade APIs, services, and reusable frameworks that integrate with enterprise platforms

• Excellent communication and collaboration skills, with the ability to partner effectively with business and technology stakeholders

Nice-to-have:

• Hands-on experience with ML engineering including model training, deployment, monitoring, and lifecycle management at scale

• Knowledge of LLMs and agentic AI workflows

• Proficiency with modern cloud data warehouses and databases (i.e. Snowflake) and experience with schema design, performance tuning, and query optimization

• Proficiency with modern DevOps/MLOps practices

About Borealis AI:

Borealis AI, an RBC Institute for Research, is a curiosity-driven research center dedicated to achieving state-of-the-art in machine learning. Established in 2016, and with labs in Toronto, Montreal, Waterloo and Vancouver, we support academic collaborations and partner with world-class research centers in artificial intelligence. With a focus on ethical AI that will help communities thrive, our machine learning scientists perform fundamental and applied research in areas such as reinforcement learning, natural language processing, Large Language Models, deep learning, and unsupervised learning to solve ground-breaking problems in diverse fields.

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.