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Dawson

Machine Learning (Summer 2027)

Toronto, ON, M5K 1G8, Canada

Internship

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Job details

Job type: Internship
Posting language: English
Posted: Aug 31, 2026

Original job description

Machine Learning (Summer 2027)

Dawson Partners (“Dawson”), based in Toronto, is a fast-growing private equity firm focused on accelerating liquidity on private equity portfolios through structured solutions. Dawson seeks to provide customized and flexible liquidity solutions for private equity investors through the use of structured solutions with existing investors or outright purchases of portfolios which are subsequently structured into different securities. Dawson currently has over $30.0B assets under management.

The Technology & Data team is seeking a Machine Learning Intern Analyst starting in May 2027 with our Toronto office. The intern will gain exposure to cutting-edge large language model (LLM) techniques, vector databases, and modern third-party frameworks such as LangChain and LangGraph, enabling them to work hands-on with real-world data, build scalable ML pipelines, and contribute to the development of next-generation finance AI solutions. They will also be encouraged to actively participate in firm-wide team meetings, investment committee discussions and projects.

Job Responsibilities:

Assist in the development of applications using Large Language Models (LLMs).
Explore and implement workflows using LangGraph and LangSmith for building and monitoring LLM-powered applications.
Work with vector databases like Pinecone to store and retrieve embeddings for semantic search and retrieval.
Contribute to the design and implementation of knowledge graphs using Neo4j.
Develop and maintain APIs using FastAPI for exposing machine learning models and functionalities.
Assist in deploying and managing applications on Google Cloud Platform (GCP).
Work with Cloud SQL for managing relational databases.
Contribute to projects involving knowledge graph construction and utilization.
Learn and apply best practices for machine learning development and deployment.
Document code and contribute to technical reports.

Education/Certification:

Currently pursuing a bachelor's or master's degree in computer, data science, or a related field.

What You Bring:

Proficiency in Python is required; experience with TypeScript and Rust is considered an asset.
Familiarity with at least one agentic AI framework or coding harness, such as LangGraph or the DeepSeek harness.
Experience building APIs with FastAPI.
A solid understanding of large language model fundamentals.
Knowledge of retrieval-augmented generation (RAG) systems, including embeddings, vector search, and hybrid search.
A collaborative team player who communicates and works well with others.
Creative, curious, and willing to approach problems differently.

Our Commitment to Diversity, Equity and Inclusion

At Dawson Partners, we are committed to being a truly diverse firm and fostering an inclusive and supportive culture. Employing a talented, diverse and inclusive workforce is more than just an obligation; it is a critical component of our growth aspirations and a competitive advantage for our Firm.

In addition, we are committed to fostering an inclusive and accessible recruitment experience where all candidates are valued, respected and supported.

If you require an accommodation for any part of the recruitment process (including alternate formats of materials, accessible meeting rooms, etc.), please let us know, so that we will work with you to meet your needs.

For additional information on Dawson Partners, please visit our website at www.dawsonpartners.com

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More about this job

Responsibilities

The intern will assist in developing and deploying LLM-powered applications, including building scalable ML pipelines and managing vector databases. They will also contribute to knowledge graph construction and maintain APIs to support the firm's finance AI solutions.

Requirements

Candidates must be currently pursuing a bachelor's or master's degree in computer science, data science, or a related field. Proficiency in Python is required, along with familiarity with agentic AI frameworks and large language model fundamentals.

Skills

Python
Large Language Models
LangChain
LangGraph
Vector Databases
Pinecone
Neo4j
FastAPI
Google Cloud Platform
Cloud SQL
Knowledge Graphs
Retrieval-Augmented Generation
TypeScript
Rust
Machine Learning Pipelines

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Large Language Models
LLM
LangChain
LangGraph
LangSmith
Vector Databases
Pinecone
Neo4j
FastAPI
Google Cloud Platform
GCP
Cloud SQL
Knowledge Graphs
Retrieval-Augmented Generation
RAG
Python
TypeScript
Rust
Finance AI
Private Equity
Data Science
API Development
Semantic Search
Embeddings
Agentic AI

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