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TORONTO, Ontario, Canada

Internship

Hybrid

Intern

RBC is a leading bank committed to becoming a client-centric, future-ready leader by harnessing data and AI. They are seeking a highly motivated Summer Intern to contribute to advanced analytics projects for risk management, applying data science and software engineering skills to impact workflows through innovative solutions.

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Responsibilities

Participate in the end-to-end development of high-impact AI solutions, from idea design and PoC to production deployment
Work closely with business users to understand their needs, translate business use cases into practical technical problems, and iterate on solutions based on feedback
Focus on building real-world applications that address business challenges, rather than conducting pure research
Continuously learn and keep up with the latest advancements in AI and related technologies, sharing knowledge with the team
Present technical solutions and project updates to both technical peers and senior managements

Qualification

Required

Hands-on experience prototyping GenAI applications, including working with foundational LLMs (e.g., GPT models via API) and transformer models (e.g., Hugging Face Transformers); familiarity with frameworks and tools (e.g., LangChain, LangGraph, LlamaIndex, Haystack), and vector databases (e.g., Weaviate, PGVector)
Hands-on experience with prompt engineering, including designing and refining prompts to optimize LLM outputs
Hands-on experience developing modular, robust, and scalable software in Python 3.x
Knowledge of modular RAG (Retrieval-Augmented Generation) and agentic systems
Knowledge of professional software engineering best practices across the software development lifecycle, including coding standards, testing methods, code reviews, and version control
Knowledge of machine learning and deep learning algorithms (e.g., supervised methods such as decision trees, gradient boosting, deep neural networks; unsupervised methods such as clustering and dimensionality reduction), as well as natural language processing techniques (e.g., TF-IDF, transformer models, embedding models)
Demonstrated willingness and ability to quickly learn and adapt to new advancements in ML/DL/GenAI
Strong logical thinking skills and attention to detail
Effective communication skills and a collaborative, team-oriented attitude
A bachelor's or master's degree or higher in computer science, engineering, statistics, or a related field is preferred

Preferred

Knowledge of embedding model fine-tuning, Model Context Protocol (MCP), LLM performance evaluation
Experience deploying GenAI applications in production environments and supporting enterprise-scale use cases
Hands-on experience implementing solutions using modern ML/DL frameworks and tools, such as PyTorch, JAX, TensorFlow, scikit-learn, or Hugging Face Transformers
Experience working in regulated or governed environments
Familiarity with financial risk management concepts

Benefits

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 do challenging work and make a difference.
Opportunities to building close relationships.

Royal Bank of Canada is a global financial institution with a purpose-driven, principles-led approach to delivering leading performance.

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