RBC Borealis is seeking a Lead Machine Learning Developer to spearhead the operationalization of advanced machine learning and GenAI solutions. In this role within the SIAI (Security Insights and AI) team, you will tackle escalating global digital threats by leveraging ML and Big Data to model behaviors and enable proactive security measures. You will also contribute to next-generation autonomous platforms, integrating large language models to enhance controls, efficiency, and compliance.
What You'll Do
- Engineer and maintain scalable data pipelines and workflows using PySpark, AWS SageMaker, Airflow, JupyterHub, and 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 platforms like Cloudera Data Lake, AWS, and OpenShift Container Platform (OCP) using the Helios CI/CD pipeline.
- Build GenAI solutions using LLMs and RAG systems (e.g., OpenAI, Cohere), vector search, and context engineering pipelines (LangChain, Semantic Kernel) to ensure AI actions are context-aware and secure.
- Apply and advocate for best practices in secure coding and MLOps CI/CD automation (Docker, Kubernetes, GitHub Actions), traceability (Langfuse), and observability (Prometheus, Grafana).
- Contribute to code reviews, collaborate with cross-functional teams including data scientists and engineers, and maintain clear technical documentation.
- Champion best practices in AI safety, privacy, regulatory compliance, and autonomous system guardrails, including model monitoring and secure deployment.
What We're Looking For
- Advanced programming skills in Python, PySpark, Unix Scripting, SQL, and PyTorch.
- 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 and experience with advanced topics like Deep Learning, Agentic AI, and Agent Orchestration.
- Experience with data preprocessing, image processing, hyperparameter optimization, feature importance analysis, transfer learning, and anomaly detection.
- Experience developing CI/CD pipelines 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), or agentic AI into production, including vector database configuration and context engineering.
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 services (Lambda, SageMaker, Bedrock).
- Familiarity with at least one workflow/AI agent orchestration platform like CrewAI, LangGraph, or N8N.
- Understanding of modern observability stacks (Grafana, Prometheus, OpenTelemetry) and secure coding practices (SAST/DAST).
Technical Stack
- Data & ML: PySpark, AWS SageMaker, Airflow, JupyterHub, RunAI, PyTorch, Databricks
- Platforms & Cloud: Cloudera Data Lake, AWS, OpenShift Container Platform (OCP)
- CI/CD & Ops: Helios, Docker, Kubernetes, OpenShift, GitHub Actions, Jenkins
- GenAI & LLMs: OpenAI, Cohere, Claude, Llama, LangChain, Semantic Kernel
- Vector Search & Storage: pgvector, Milvus, Pinecone
- Observability & Tools: Langfuse, Prometheus, Grafana, OpenTelemetry
- Data Stores: Snowflake, Postgres, MongoDB
- APIs & Frameworks: REST, GraphQL, FastAPI, Django
- Additional Tools: HuggingFace, DeepSpeed, Triton, ONNX, AWS Lambda, AWS Bedrock, CrewAI, LangGraph, N8N
Team & Environment
You will be a key member of the SIAI (Security Insights and AI) team, working in a dynamic and collaborative environment focused on high-impact security solutions.
Benefits & Compensation
- A comprehensive Total Rewards Program including bonuses, 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 and take on progressively greater accountabilities.
- Opportunities to build close relationships with clients.
- Access to a variety of job opportunities across business and geographies.
Work Mode
This role is based in Toronto, Canada and follows a local in-office work mode.
At RBC, we believe an inclusive workplace with diverse perspectives is core to our continued growth. We strive to maintain a workplace where employees feel supported to perform at their best, collaborate effectively, drive innovation, and grow professionally through policies and programs based on respect, belonging, and opportunity for all.
