Lead Machine Learning Developer

What is the opportunity?

As a Lead ML Developer at RBC, you’ll spearhead the operationalization of advanced machine learning (ML) 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 will 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 design, build, and 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, 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.
• 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, AWS, OpenShift Container Platform (OCP), using Helios on Actions CI/CD pipeline.
• Build GenAI solutions using LLMs and RAG systems (OpenAI, Cohere, Claude, Llama), vector search (pgvector, Milvus, Pinecone), and advanced context engineering pipelines (LangChain, Semantic Kernel) to ensure AI actions are context-aware, secure, and aligned with enterprise data.
• 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

• Advanced programming skills of the following languages: Python, PySpark, Unix Scripting, SQL, PyTorch etc.
• Strong experience building data pipelines and APIs with Spark, Databricks, Airflow, SQL (Snowflake, Postgres), and NoSQL (MongoDB); experience with REST, GraphQL, FastAPI, Django.
• Solid knowledge of general Machine Learning concepts both in theory and application and 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.
• Demonstrated hands-on experience deploying LLMs, RAG systems, agent orchestration frameworks (e.g., LangChain, CrewAI, AutoGen), or agentic AI into production, including vector database configuration (pgvector, Milvus, Pinecone, FAISS), and context engineering for autonomous workflows.

Nice to Have

• Experience fine-tuning LLMs (e.g., LoRA, PEFT), prompt engineering, and large-scale model deployment using HuggingFace, DeepSpeed, Triton, or ONNX. Familiarity with AWS cloud environments services (Lambda, SageMaker, Bedrock, etc).
• 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 it 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

• A world-class training program in financial services

• Opportunities to do challenging work

• Opportunities to take on progressively greater accountabilities

• Opportunities to building close relationships with clients

• Access to a variety of job opportunities across business and geographies.

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Job Skills

Big Data Management, Data Mining, Data Science, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming Languages

Additional Job Details

16 YORK ST:TORONTOTorontoCanada37.5Full timeTECHNOLOGY AND OPERATIONSRegularSalaried2026-01-202026-02-02

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.

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.