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Entry Level Machine Learning Engineer Jobs in Quebec

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software ...

As a Machine Learning Operations Software Engineer at Ubisoft Montréal, you will help build reliable and scalable systems that protect the trust and safety of our players . You will join the Player ...

You will contribute to the implementation of machine learning models, intelligent agents, AI copilots, and data-driven applications while following CAE engineering standards and best practices.

Work closely with machine learning engineers and data engineers to design, build, and test models. * Develop efficient and scalable algorithms for training and inference of generative models ...

AI/ML Engineer - Remote

Montreal, QC · Remote

$200 - $350/hr

You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications. Key Responsibilities * Design, implement, and ...

Build predictive, generative, and agentic AI solutions using sound machine learning, evaluation, and analytics practices. * Engineer reusable, platform-ready components, prompts, connectors ...

Research Associate

Sherbrooke, QC · On-site

CA$35.37/hr

PhD in Computer Science, Information Science, or Engineering. * A minimum of five peer-reviewed publications in data mining, machine learning, AI, or cybersecurity. * At least two years of ...

PhD in Computer Science, Information Science, or Engineering. * A minimum of five peer-reviewed publications in data mining, machine learning, AI, or cybersecurity. * At least two years of ...

... analytics, engineering, product) on high-impact end-to-end use cases (anomaly detection ... Utilize machine learning and advanced statistical methods to identify trends and patterns in ...

... analytics, engineering, product) on high-impact end-to-end use cases (anomaly detection ... Utilize machine learning and advanced statistical methods to identify trends and patterns in ...

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Entry Level Machine Learning Engineer information

See Quebec salary details

$21K

$87.2K

$186K

How much do entry level machine learning engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for entry level machine learning engineer in Quebec is $87,195.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,000.00 and $98,500.00 per year, depending on experience, location, and employer.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are the most commonly searched types of Machine Learning Engineer jobs in Quebec?

The most popular types of Machine Learning Engineer jobs in Quebec are:

What are popular job titles related to Entry Level Machine Learning Engineer jobs in Quebec?

For Entry Level Machine Learning Engineer jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Entry Level Machine Learning Engineer jobs in Quebec look for?

The top searched job categories for Entry Level Machine Learning Engineer jobs in Quebec are:

Infographic showing various Entry Level Machine Learning Engineer job openings in Quebec as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $87,195 per year, or $41.9 per hour.

Machine Learning Engineer - Remote

YO AI Labs

Montreal, QC • Remote

$80 - $120/hr

Full-time

Posted 7 days ago


Job description

Senior Software Engineer

Job Type: Contractor (~15 hours/week)
Location: Remote

Job Summary

We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software engineering tasks using Model Context Protocol (MCP) tools.

You will design reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization. No prior AI experience is required.

Key Responsibilities
  • Create reinforcement learning environments for software engineering tasks.
  • Design tasks involving bug fixing, feature development, refactoring, and performance optimization.
  • Build deterministic verification systems and golden reference solutions.
  • Evaluate AI agents' ability to reason through complex codebases and use MCP tools effectively.
  • Develop realistic, reproducible software engineering scenarios.
  • Ensure tasks accurately measure coding ability, problem-solving, and tool usage.
  • Document solutions and provide clear technical feedback.
Required Skills
  • Strong proficiency in Python 3, Java, Rust, C++, or TypeScript.
  • Strong understanding of algorithms and data structures.
  • Experience with bug fixing and debugging complex software issues.
  • Proven experience in feature implementation and codebase refactoring.
  • Strong knowledge of performance optimization and tuning.
  • Excellent written and verbal communication.
  • Strong attention to detail.
Preferred Qualifications
  • Experience working with large-scale or distributed codebases.
  • Familiarity with AI/ML systems is a plus but not required.
  • Experience with rigorous code reviews and software engineering best practices.
  • Experience working effectively in remote or cross-functional teams.
Hiring Process
  1. Submit an application and screening questions.
  2. Complete an AI interview (~30 minutes).
  3. Complete a technical assessment, if required.
  4. Hiring Manager review.
Compensation

Compensation is output-based, with payment provided per task that meets project specifications. Minimum weekly submission requirements may apply.

Availability

Selected experts should be prepared to begin their first tasks within 24–48 hours of completing onboarding.