What is the opportunity?
As a Senior ML Developer at RBC, you’ll spearhead the operationalization of advanced machine learning (ML), User Behavior Analytics (UBA) and GenAI solutions within SIAI (Security Insights and AI) team. In this role, you’ll address the escalating threats in our global digital landscape by leveraging ML and Big Data technologies to model and predict behaviors, enabling proactive threat detection and response. You may also contribute to next-gen autonomous/semi-autonomous AI platforms, integrating large language models (LLMs) and GenAI to enhance detective/preventive controls, operational efficiency, and regulatory compliance.
You’ll guide design process, and help deploy scalable ML pipelines/agentic systems to deliver production-grade AI solution for Cyber, Fraud, Risk, and Security utilize on-prem/cloud-native tools (GPU AI Farm, Neo4j, Kubernetes, Docker, AWS/Azure) to maintain robust, secure, and compliant production environments.
What will you do?
Engineer and maintain scalable data pipelines and workflows using PySpark, AWS SageMaker, Airflow, JupyterHub, RunAI, Neo4j.
Build pipeline to integrate ML/UBA detections into a graph knowledgebase (Neo4j) to enable event correlation and run analytical query.
Optimize Spark job performance through advanced tuning, resource management, and cost-efficient scalability. Deploy batch and real-time inference models with robust monitoring.
Deploy, manage, and optimize ML and Agentic applications across multiple platform such as Cloudera Data Lake, Neo4j Graph DB, AWS, OpenShift Container Platform (OCP), using Helios on Actions CI/CD pipeline.
Apply and advocated for best practices in secure coding and MLOps CI/CD automation (Docker, Kubernetes, OpenShift, GitHub Actions, Jenkins), traceability (Langfuse) and observability (Prometheus, Grafana).
Contribute to code reviews, collaborate with data scientists and engineers, front and backend engineers and ML engineers, and maintain clear technical documentation.
Champion best practices in AI safety, privacy, regulatory compliance, and autonomous system guardrails, including model monitoring, fallback mechanisms, and secure deployment in regulated environments.
What do you need to succeed?
Must Have:
2+ years of experience, and advanced programming skills of the following languages: Python, PySpark, Unix Scripting, SQL, PyTorch etc.
Strong experience building data pipelines and APIs with Spark, Airflow, Neo4j, SQL (Snowflake, Postgres), and NoSQL (MongoDB); experience with REST, FastAPI/Django.
Hands-on experience with Neo4j and cypher graph query language or other similar graph db.
Foundational knowledge of general Machine Learning concepts both in theory and application and some experience with advanced topics like Deep Learning, Agentic Ai and Agent Orchestration etc.
Experience with data preprocessing, image processing, hyperparameter optimization, code optimization feature importance analysis, transfer learning, and anomaly/outlier detection.
Experience developing CI/CD pipeline for AI/ML models, deploying, and supporting models in production.
Nice to Have
Familiarity with AWS cloud environments services (Lambda, SageMaker, Bedrock, etc).
Hands -on experience deploying LLMs, RAG systems, agent orchestration frameworks (e.g., LangChain, CrewAI, AutoGen), or agentic AI into production, and context engineering for autonomous workflows.
Familiarity with atleast one workflow/AI agent orchestration platforms like CrewAI, LangGraph, N8N, etc.
Understanding of modern observability stacks (Grafana, Prometheus, OpenTelemetry) and secure coding practices (SAST/DAST).
What’s In For You?
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.
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
Opportunities to take on progressively greater accountabilities.
Access to a variety of job opportunities across business and geographies.
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Job Skills
AWS Cloud Computing, Big Data Technologies, Data Science, Deep Learning, Generative AI, Generative AI Agents, GraphDB, Kubernetes, Machine Learning (ML), Neo4j Graph Database, PySpark, Python (Programming Language), RAG Pipeline, Structured Query Language (SQL)
Additional Job Details
16 YORK ST:TORONTO
Toronto
Canada
37.5
Full time
TECHNOLOGY AND OPERATIONS
Regular
Salaried
2026-05-28
2026-06-30
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.
