1

Junior Machine Learning Engineer Jobs in Quebec (NOW HIRING)

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 ...

... machine learning methods: Data manipulation and transformation Model selection, training, and validation Programming and integration into our software product suite * Documenting and testing ...

... Machine Learning / AI en production . Vous agirez en propriétaire end-to-end des pipelines de ... engineering orientée performance et valeur métier Profil recherché Expérience Minimum 5 ans ...

Mission We are seeking a Python-focused Data Engineer to bridge the gap between data infrastructure ... Collaborate with data scientists to architect, package, configure, and deploy machine learning ...

Mission We are seeking a Python-focused Data Engineer to bridge the gap between data infrastructure ... Collaborate with data scientists to architect, package, configure, and deploy machine learning ...

Mission We are seeking a Python-focused Data Engineer to bridge the gap between data infrastructure ... Collaborate with data scientists to architect, package, configure, and deploy machine learning ...

Lead AI/ML Engineer

Montreal, QC · On-site

CA$130K - CA$160K/yr

Mentor and guide junior AI/ML engineers on data modeling and algorithm performance tuning * Partner with Data Science, ML, and Backend teams to productionize machine learning features in Snowflake

You will work closely with a team of data scientists and data engineers to deploy solutions and drive innovation using machine learning and NLP techniques. The ideal candidate has a deep ...

We are seeking a senior distributed machine learning (ML) research developer to join our team working on a novel AI safety agenda. In this role, you will work closely with ML research scientists to ...

Work with our machine learning engineers to put cutting edge deep learning algorithms in production. * Develop tools and contribute to open source wherever possible. * Adopt problem solving as a way ...

Designing and building end-to-end machine learning and statistical models that solve high-stakes ... Partnering with client teams and data engineers to ensure models are production-ready, scalable ...

We are seeking a senior machine learning (ML) research developer to join our team working on a novel AI safety agenda. In this role, you will work closely with ML research scientists to solve ...

next page

Showing results 1-20

Junior Machine Learning Engineer information

See Quebec salary details

$26K

$119.2K

$207.5K

How much do junior machine learning engineer jobs pay per year?

As of Jul 2, 2026, the average yearly pay for junior machine learning engineer in Quebec is $119,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,500.00 and $149,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a Junior Machine Learning Engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What is the difference between Junior Machine Learning Engineer vs Data Scientist?

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What does a junior machine learning engineer do?

A junior machine learning engineer assists in developing, testing, and deploying machine learning models under supervision. They work with data preprocessing, feature engineering, and use tools like Python and libraries such as TensorFlow or scikit-learn to support AI projects. This role often requires foundational knowledge of algorithms, programming, and data analysis.

How much does a junior machine learning engineer make?

A junior machine learning engineer typically earns between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level often requires advanced degrees, specialized certifications, and a strong track record of impactful projects.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. These positions usually involve leadership, strategic planning, and significant experience, and they tend to be found in large tech companies or specialized AI firms.

What Does a Junior Machine Learning Engineer Do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

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 Junior Machine Learning Engineer jobs in Quebec? For Junior Machine Learning Engineer jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning Engineer jobs in Quebec look for? The top searched job categories for Junior Machine Learning Engineer jobs in Quebec are:
What cities in Quebec are hiring for Junior Machine Learning Engineer jobs? Cities in Quebec with the most Junior Machine Learning Engineer job openings:
Infographic showing various Junior Machine Learning Engineer job openings in Quebec as of June 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $119,158 per year, or $57.3 per hour.

Generative AI Engineer

Apertera

Montreal, QC • On-site

Full-time

Posted 7 days ago


Job description

Generative AI EngineerAbout Apertera

Apertera is leading the evolution of language solutions for high-stakes content. We partner with enterprises as an extension of their teams, combining professional expertise with Adaptive AI technology that is continuously refined by client context.

For more than twenty years, Apertera has set the bar for legal, financial, and regulatory translation, serving the most rigorous buyers, including over 75% of major national Canadian law firms, all major banks, and leading securities regulators.
Apertera is Canadian-owned, ISO 17100 and SOC 2 certified.

Our core values: 

  • Innovation
  • Dedication
  • Fanatical commitment to quality and service
  • Resourcefulness
  • Collaboration
About the Role

We are looking for a Generative AI Engineer to develop our next-generation intelligent translation and translation-related service engine, using Generative AI (GenAI) and Large Language Model (LLM) technologies. You will report to the team lead in AI Innovation, develop and implement state-of-the-art algorithms by fast prototyping, and collaborate with the software team to deploy models. We expect our Generative AI Engineer to to work at the intersection of LLM engineering, machine translation, cloud infrastructure, and evaluation. You'll play a pivotal role in pushing the boundaries of applying GenAI to translation scenarios and create innovative solutions.

Responsibilities
  • Implement state-of-the-art LLM techniques including continued pre-training, instruction fine-tuning, preference alignment, and LLM deployment.
  • 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, leveraging deep learning frameworks such as TensorFlow or PyTorch and optimizing performance on diverse hardware platforms.
  • Train and evaluate generative models using appropriate metrics and benchmarks, fine-tuning model parameters, architectures, and hyperparameters to optimize performance, stability, and generalization.
  • Built end-to-end prototypes that are production ready.
  • Work closely with software and DevOps engineers to deploy GenAI models.    
  • Document code, algorithms, and experimental results, following best practices for reproducibility, version control, and software engineering, and contributing to internal knowledge sharing and continuous improvement initiatives.
Requirements
  • Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or related fields. A Master’s degree is preferred.
  • 2+ years of industry experience developing GenAI and LLM applications is preferred.
  • Proficiency in Python programming and software development practices, with experience in building and maintaining scalable, production-grade software systems.
  • Working knowledge and project-based record of all of the following: context engineering, RAG, harness engineering.
  • Working knowledge and project-based record of at least one of the following is a plus: LLM post-training, APO, agentic workflow.
  • Strong problem-solving skills, attention to detail, and the ability to work independently and collaboratively in a fast-paced environment.
  • Hands-on experience with Huggingface APIs or Amazon Bedrock. 
  • Expert skills of Python, including PyTorch, TensorFlow, Pandas, etc.
  • Experience with cloud platforms like AWS, GCP, or Azure 
  • Excellent problem-solving skills, critical thinking, and the ability to work independently and collaboratively in a fast-paced environment.
  • Strong communication skills, with the ability to articulate complex technical concepts effectively and work cross-functionally with diverse teams.
  • Self-driven, self-motivated with excellent time management skills
  • Excellent organizational, communication, and interpersonal skills
  • Ability to adapt to shifting priorities without compromising deadlines and momentum.

 

Powered by JazzHR

CaTtRWwyiB