Staff AI/ML Engineer
Indexed description
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 ongoing development in areas such as reinforcement learning, unsupervised learning and computer vision. You can find out more about our research areas at rbcborealis.com.
Your responsibilities include:
- Designing, building, and operating scalable ML model-serving infrastructure using SageMaker, MLflow, or equivalent platforms, ensuring low-latency, high-throughput inference in production—without involvement in upstream model training.
- Architecting and maintaining real-time data and feature pipelines using Kafka and streaming frameworks to support online model serving and event-driven ML workflows.
- Developing and maintaining robust backend services in Python that expose ML capabilities to downstream consumers via reliable, well-documented APIs.
- Owning containerized deployment of ML workloads on OpenShift Container Platform (OCP4) / Kubernetes, including
- resource optimization, autoscaling, and rollout strategies.
- Building and maintaining CI/CD pipelines (GitHub Actions) for model validation, packaging, and deployment, embedding quality gates and automated testing throughout.
- Instrumenting ML services with comprehensive observability—metrics, logs, and traces—using Datadog, Dynatrace,
- Prometheus, or equivalent tooling; driving incident response and blameless post-mortems
- Strong, production-proven experience with ML model serving and lifecycle management using SageMaker, MLflow, or comparable platforms.
- Expert-level Python skills for backend service development, ML pipeline engineering, and automation scripting.
- Deep hands-on experience with Apache Kafka and streaming/event-driven architectures for real-time feature pipelines and model inference.
- In-depth knowledge of OpenShift Container Platform (OCP4) / Kubernetes for deploying and operating containerized ML workloads.
- Proven experience building and maintaining CI/CD pipelines with GitHub Actions or equivalent tools for ML model delivery.
- Hands-on expertise with observability platforms such as Datadog, Dynatrace, or Prometheus applied to distributed ML systems.
- Demonstrated ability to design scalable distributed backend systems that operate reliably under high load in hybrid cloud environments (AWS / Azure / on-prem).
- Experience with site reliability practices: SLOs/SLIs, alerting, incident management, and capacity planning for ML services.
- Proficiency with MongoDB in production environments for storing model metadata, feature stores, or application state.
- Experience with Elasticsearch for log aggregation, search, and ML-adjacent analytics use cases.
- Familiarity with JavaScript or Go for building lightweight platform tooling or internal developer portals.
- Background in audio processing pipelines—speech recognition, audio feature extraction, or real-time audio streaming—for multimodal AI applications.
- Exposure to agentic AI systems, LLM orchestration frameworks, or self-hosted large language model infrastructure.
- 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.
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.
#TECHPJ
Job Skills
AI Ops, Amazon SageMaker, Apache Kafka, Autoscaling, Big Data Management, CI/CD, Datadog, Data Mining, Data Science, Deep Learning, Dynatrace APM, Machine Learning (ML), Microsoft Azure, MLflow, ML Integration, MongoDB, Predictive Analytics, Programming Languages, Python (Programming Language), Red Hat OpenShift
Additional Job Details
Address:
407 8 AVE SW:CALGARY
City:
Calgary
Country:
Canada
Work hours/week:
37.5
Employment Type:
Full time
Platform:
TECHNOLOGY AND OPERATIONS
Job Type:
Regular
Pay Type:
Salaried
Posted Date:
2026-04-24
Application Deadline:
2026-06-26
Note: 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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