ML Engineer

RBC • Toronto, ON

1d • Hybrid

About The Position

Join the Shared Platform Services (SPS) team as we revolutionize operational processes within Technology Infrastructure by delivering enterprise-grade, data-intensive AI and GenAI solutions. We are looking for a talented and adaptable ML Engineer to help design, build, and maintain cutting-edge solutions for key stakeholders across Technology & Operations, including Digital Platform Services, Engineering Transformation Services, SRE Operations Teams, and TI Platforms. In this role, you will work at the forefront of AI and machine learning infrastructure, focusing on LLM developments as well as GenAI infrastructure. You’ll also play a critical role in the end-to-end software development lifecycle (SDLC), from gathering requirements and designing solutions to development, testing, deployment, and knowledge transfer to support teams. Working in a fast-paced, collaborative environment, you’ll partner closely with data leads and business stakeholders to ensure that our solutions are fit for purpose and operate seamlessly. This is a unique opportunity to grow your expertise in machine learning infrastructure and work with a passionate, high-performing team committed to bringing AI and GenAI solutions to enterprise at scale.

Requirements

• Experience building and maintaining data ingestion pipelines
• In-depth knowledge of the Python application deployment lifecycle, including CI/CD processes.
• Hands-on experience deploying hybrid environments on on-premise and cloud platforms, including RedHat OpenShift and Azure.
• Proven proficiency in programming languages such as Python, and Java.
• Experience working with relational databases (e.g., MSSQL, PostgreSQL, MySQL), including expertise in profiling data and writing/optimizing SQL queries.
• Familiarity with non-relational databases e.g., Elasticsearch, MongoDB.
• Strong written and verbal communication skills, with the ability to create compelling presentations and effectively collaborate with stakeholders.

Nice To Haves

• Experience with data analytics and monitoring platforms, such as Splunk, Dynatrace, Moog, PromQL, and Grafana Enterprise Metrics (GEM).
• Familiarity with machine learning frameworks such as PyTorch, TensorFlow and/or scikit-learn.
• Previous experience with MLOps orchestration tools such as AirFlow, KubeFlow, or MetaFlow.
• Experience working in agile teams using methodologies like Scrum or Kanban.

Responsibilities

• Implement LLM agents and deploy them on hybrid cloud environment
• Design, develop, and implement AI-enabled data ingestion applications and machine learning systems
• Collaborate with peers to write, troubleshoot, enhance, and document high-quality code aligned with strategic initiatives and detailed requirements.
• Partner with internal teams across RBC to deliver software features, resolve issues, and implement bug fixes.
• Ensure seamless integration of machine learning applications into enterprise-grade infrastructure while maintaining high performance and reliability.

Benefits

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact
• Work in a dynamic, collaborative, progressive, and high-performing team
• A world-class training program in financial services
• Flexible work/life balance options
• Opportunities to do challenging work

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed