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Research Assistant Machine Learning Jobs in Toronto, ON

United Airlines

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$105K - CA$125K/yr

... assist with data-related technical issues and support their data infrastructure needs. - Create ... The role of a machine learning professional involves applying machine learning techniques and ...

THOMSON REUTERS

Research Engineer

Toronto, ON · Hybrid

We are seeking a Research Engineer who willbringexpertiseinAI and ML andisinterestedinbuilding data ... Ability to understand, apply,integrateand deploy Machine Learning capabilities and techniques into ...

Waabi

Research Scientist

Toronto, ON · On-site

CA$158K - CA$269K/yr

Submit and publish work externally at top machine learning, computer vision, and robotics ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Waabi

Research Scientist, Simulation Agents

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

Masters/PhD in machine learning, computer science, engineering, or a related field. * Strong ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

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Research Assistant Machine Learning information

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$33

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How much do research assistant machine learning jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for research assistant machine learning in Toronto, ON is $33.23, according to ZipRecruiter salary data. Most workers in this role earn between $15.37 and $47.72 per hour, depending on experience, location, and employer.

What is a research assistant machine learning?

A Research Assistant in Machine Learning supports research projects by implementing algorithms, analyzing data, and conducting experiments to advance AI models. They assist senior researchers by preprocessing datasets, developing machine learning models, and evaluating their performance. Responsibilities may also include coding, literature reviews, and writing research papers. This role is typically found in academia, research labs, or industry R&D teams. Strong programming skills, statistical knowledge, and familiarity with ML frameworks like TensorFlow or PyTorch are essential.

What types of projects might a research assistant machine learning typically work on?

As a Research Assistant in Machine Learning, you may be involved in projects such as developing and evaluating predictive models, processing and analyzing large datasets, and assisting in the publication of research findings. Your work could contribute to applications like natural language processing, computer vision, or recommendation systems, depending on the focus of the research group. You’ll often collaborate closely with senior researchers, data scientists, or PhD students, allowing you to participate in brainstorming sessions, code development, and experimental design. This experience provides valuable exposure to cutting-edge technology and can serve as a strong foundation for a research or industry career in machine learning.

What are the key skills and qualifications needed to thrive as a research assistant machine learning?

To thrive as a Research Assistant Machine Learning, you need a solid understanding of machine learning algorithms, programming skills (especially in Python or R), and a background in statistics or computer science, often supported by a bachelor’s or master’s degree. Experience with frameworks such as TensorFlow, PyTorch, and data analysis tools, as well as familiarity with version control systems like Git, is highly beneficial. Strong problem-solving abilities, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills ensure you can contribute meaningfully to research projects, analyze complex datasets, and communicate findings effectively within interdisciplinary teams.

What are popular job titles related to Research Assistant Machine Learning jobs in Toronto, ON?

For Research Assistant Machine Learning jobs in Toronto, ON, the most frequently searched job titles are:

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What cities near Toronto, ON are hiring for Research Assistant Machine Learning jobs?

Cities near Toronto, ON with the most Research Assistant Machine Learning job openings:

Research Assistant Machine Learning jobs near you
Infographic showing various Research Assistant Machine Learning job openings in Toronto, ON as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 76% Full Time, 20% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $69,124 per year, or $33.2 per hour.

Machine Learning Engineer - Enterprise

Toronto, ON

Boson AI
See more jobs at Boson AIexternal

CA$150K - CA$400K/yr

Full-time

Re-posted yesterday

Job description

About Boson AI: At Boson AI, we are not just building AI solutions; we are pioneering the future of enterprise AI. Driven by a passion for cutting-edge AI research, particularly in the transformative areas of large language models and agentic systems, our mission is to tackle the most complex real-world problems for businesses and unlock significant value. We are a dynamic and collaborative team of researchers and engineers who thrive on pushing the boundaries of what's possible, dedicated to delivering high-quality, reliable products that seamlessly integrate into the fabric of enterprise workflows and set new industry standards.
 
About the Role: We are seeking a skilled, detail-oriented, and passionate Machine Learning Engineer to join our enterprise team. In this pivotal role, you will be at the forefront of developing and deploying groundbreaking AI solutions. This involves integrating advanced language/voice/vision models, mastering fine-tuning techniques, building sophisticated workflows and platforms, and pioneering innovative agentic approaches. You will immerse yourself in challenging problems that demand a deep understanding of model behavior, meticulous implementation, and an unwavering commitment to quality and reliability in enterprise environments. A key and exciting aspect of this role is contributing to the architecture and implementation of intelligent systems where AI agents can perform complex tasks autonomously, interacting with diverse data sources and tools, as we collectively move towards building truly cohesive and powerful AI capabilities for our clients.
Responsibilities
  • Deliver solutions end to end that meet the needs of our customers - understanding user pain points, scoping product specs, and designing and building LLM-powered software.
  • Benchmark the model, and help write evals for customers to identify model weaknesses.
  • Develop and deploy modern search systems (e.g., RAG, DeepSearch) to enhance model performance, grounding, and the ability to utilize enterprise-specific knowledge.
  • Implement and optimize techniques for fine-tuning and align large models on domain-specific data.
  • Ensure the quality, reliability, security, and scalability of models and agentic systems through meticulous attention to detail, diligent execution, and continuous monitoring in demanding enterprise settings.
  • Integrate individual AI components into a scalable platform.
Qualifications
  • Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field, or equivalent practical experience.
  • Strong contribution record on GitHub. Please include your GitHub link in your application.
  • Experience working with large language or multimodal models and their applications.
  • Experience implementing and working with search systems.
  • Proven ability to pay close attention to detail and prioritize quality, reliability, and security in technical work.
  • Proficiency in programming languages (e.g., Python, Rust, TypeScript or Go) and relevant ML frameworks (e.g., PyTorch, JAX).
  • Demonstrated ability to design, chain, or orchestrate multiple models (especially LLMs) to create multi-step pipelines or workflows for task automation.
Bonus Points
  • Experience developing or contributing to agentic AI products or systems.
  • Experience with cloud platforms (AWS, GCP, Azure) and MLOps practices.
  • Familiarity with distributed training and inference techniques.
  • Experience with system design, API development, and building scalable infrastructure for deploying and managing AI models or agentic systems.
  • Understanding of enterprise software integration patterns and data security considerations.
  • Solid understanding of HTTP protocol and real-time communication protocols (e.g., WebRTC) for voice AI. 
  • Excellent problem solving skills.
  • Ability to work independently and drive projects forward in a fast-paced environment
$150,000 - $400,000 a year
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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