data scientist

TD Bank; Montreal (administrative region); On-site; CAD 45,000 - 75,000; Full time

Job summary

A leading financial institution based in Canada is offering an internship for an Applied Machine Learning Scientist, focusing on model validation. Candidates should be enrolled in a Master's program and have significant knowledge in AI/ML, especially Generative AI and Deep Learning. The role requires excellent communication skills, as findings will need to be conveyed to both technical and non-technical audiences. The internship runs for six months, offering a competitive salary range.

Qualifications

• Currently enrolled Master's with the intention to return to school.
• Strong knowledge of AI/ML methodologies, particularly Generative AI.
• Excellent communication skills for technical reporting.

Responsibilities

• Validate AI/ML models including Generative AI usage.
• Stay updated on advancements in the Generative AI field.
• Communicate findings clearly to various stakeholders.

Skills

AI/ML methodologies

Generative AI

Deep Learning

NLP

Python

Education

Master’s degree in Computer Science, Machine Learning, or related field

Tools

PyTorch

TensorFlow/Keras

LangChain/LangGraph

HuggingFace

Azure Databricks

Azure MLFlow

Job description

Risk Management - Applied Machine Learning Scientist, Model Validation Intern Co-op (Summer)

Employer: TD Bank

Role Type: Internship/Co‑op

Work Term: Summer / Term 3

Work Location: Toronto, Ontario, Canada

Hours: 37.5

Pay: $45,700 - $74,400 CAD

Job Description:

TD Model Validation (MV) group is responsible for the independent review/validation and approval of models. The Artificial Intelligence/Machine Learning (AI/ML) MV team is responsible for the validation of all AI/ML models such as Generative AI, Agentic AI, Deep Learning for Tabular Data, used across the Bank for various use cases.

• Validate: AI/ML models, particularly Generative AI, including RAG and/or Agentic AI use cases. Provide effective challenge and review.
• Stay up to date: Advancements in the field of Generative AI, major publications, large language models, evaluation metrics, technology stacks, and datasets.
• Communicate findings and recommendations to both technical and non‑technical stakeholders.

Qualifications:

• Currently enrolled in a Master’s degree in Computer Science, Machine Learning, Engineering, Statistics, Mathematics, or related field and intend to return to school at the start of your work term.
• Experience with and strong knowledge of AI/ML methodologies including Generative AI, Agentic AI, Deep Learning, modern NLP, Retrieval‑Augmented Generation (RAG), Transformers.
• Experience with Deep Learning and Generative AI technology stacks and libraries such as PyTorch, TensorFlow/Keras, LangChain/LangGraph, HuggingFace, Azure Databricks, Azure MLFlow etc.
• Proficiency in programming languages such as Python.
• Excellent verbal and written communication skills; the position requires writing clean technical reports.

Additional Information:

Position is a 6‑month work term, commencing May 4th – August 21st 2026. Applications must include a transcript, cover letter (one‑letter‑sized page or less), and a resume (maximum of 2 pages). We welcome all applications; however, only qualified candidates will be contacted for an interview.