1

Machine Learning Developer Intern Jobs in Quebec

... machine-human interfaces for mine hoist systems. You will be part of ABB Canada's Process ... You'll grow through meaningful work, continuous learning, and support that's tailored to your goals.

New

Electro-Magnetic intern

Boucherville, QC · Hybrid

CA$24 - CA$27.75/hr

... engineering, preferred electrical machine and drive domain Skills and Competencies * Basic ... Strong learning ability and proactive Intership details The internship is full-time during the fall ...

As an electrical engineering intern within our electrification division in Montreal, you will have ... You'll grow through meaningful work, continuous learning, and support that's tailored to your goals.

New

... Methods and Programming Director, the intern will support the programmers. Responsibilities ... Determine required machining steps in collaboration with the Methods Department. * Read and ...

... Methods and Programming Director, the intern will support the programmers. Responsibilities ... Determine required machining steps in collaboration with the Methods Department. * Read and ...

next page

Showing results 1-20

Machine Learning Developer Intern information

How do Machine Learning Developer Interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What does a Machine Learning Developer Intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

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

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

Développeur en apprentissage automatique III / Machine Learning Developer III

Développeur en apprentissage automatique III / Machine Learning Developer III

Trane Technologies

Montreal, QC

Full-time

Posted 17 days ago


Trane Technologies rating

8.0

Company rating: 8.0 out of 10

Based on 291 frontline employees who took The Breakroom Quiz

133rd of 528 rated manufacturers


Job description

Be a part of our mission! As a world leader in creating comfortable, sustainable, and efficient climate solutions for buildings, homes and transportation, it's our responsibility to put the planet first. For us at Trane Technologies, and through our businesses including Trane® and Thermo King,  sustainability is not just how we do business—it is our business.  Do you dare to look at the world's challenges and see impactful possibilities?  Do you want to contribute to making a better future?  If the answer is yes, we invite you to consider joining us in boldly challenging what's possible for a sustainable world.

Learn about our benefits designed for you to Thrive at work and at home. 

We boldly go.

Where is the work:

Our BrainBox AI Workplace Presence model dedicates specific in-office days each month to focus on relationships, learning and innovation.

Ce que vous ferez :

  • Mise en œuvre de cadres : Participer activement à la conception et à l’implantation concrète de cadres d’IA évolutifs adaptés aux projets actuels et futurs de BrainBox AI.

  • Déploiement de modèles : Collaborer étroitement avec les ingénieurs et chercheurs en AA afin de combler l’écart entre un modèle entraîné et un service déployé, en résolvant les frictions d’ingénierie liées à la mise en production.

  • Surveillance et détection de dérive : Concevoir et déployer le « système immunitaire » de nos modèles — des systèmes qui suivent la dégradation des performances et détectent de façon proactive la dérive des données et des concepts.

  • Soutien technique et programmation : Agir comme ressource de haut niveau en programmation d’IA et fournir un soutien technique à l’équipe élargie afin d’assurer l’atteinte précise des jalons de projet.

  • Initiatives interfonctionnelles : Faire évoluer les méthodologies existantes et développer de nouvelles techniques pour des initiatives couvrant différentes fonctions d’ingénierie et de recherche.

  • Intelligence des données : Repérer et interpréter des tendances complexes dans les ensembles de données afin d’optimiser la performance des algorithmes selon les besoins d’affaires réels.

  • Excellence du code : Rédiger un code exceptionnellement propre, testable et facile à déboguer. Promouvoir la documentation et les meilleures pratiques de développement logiciel tout au long du cycle de vie de l’AA.

Ce dont vous aurez besoin pour réussir :

  • Baccalauréat ou maîtrise en génie logiciel, en informatique ou équivalent.

  • De 5 à 8+ ans d’expérience en génie logiciel, avec une forte spécialisation dans le déploiement et la maintenance de systèmes d’apprentissage automatique.

  • Maîtrise avancée de Python et de la programmation orientée objet (POO), essentielle.

  • Solide expérience des environnements AWS (Lambda, SageMaker, tables Glue, SQS/SNS, API Gateway, CloudWatch) et gestion des rôles IAM pour des déploiements sécurisés.

  • Expertise avec pytest et les cadres de tests unitaires afin d’assurer la fiabilité du code.

  • Connaissance approfondie des environnements Linux et forte propension à automatiser les tâches et flux de travail répétitifs.

  • Bonne compréhension des modèles de déploiement en AA et des architectures LLM actuelles.

  • Capacité à expliquer efficacement des concepts d’ingénierie complexes à des collègues aux profils techniques variés.

  • Membre d’équipe proactif agissant comme personne-ressource, partageant ses connaissances et résolvant efficacement les problèmes liés aux modèles.

Exigences linguistiques

Le bilinguisme français-anglais est requis.

En plus de la maîtrise du français, les personnes retenues doivent posséder une compétence professionnelle complète en anglais afin de soutenir et de collaborer avec des clients, collègues et/ou divers intervenants anglophones.

***English Follows

What you will do:

  • Framework Implementation: Actively participate in the design and hands-on implementation of scalable AI frameworks tailored for BrainBox AI’s ongoing and future projects.

  • Model Deployment: Partner closely with ML engineers and researchers to bridge the gap between a trained model and a deployed service, solving the engineering "friction" that arises during productionization.

  • Monitoring & Drift Detection: Build and deploy the "immune system" for our models—systems that track performance decay and proactively detect data and concept drift.

  • Technical Support & Programming: Serve as a high-level resource in AI programming, providing technical support to the broader team to ensure project milestones are met with precision.

  • Cross-Functional Initiatives: Help evolve existing methodologies and develop new techniques for initiatives that span across different engineering and research functions.

  • Data Intelligence: Identify and interpret complex patterns within datasets to refine and enhance algorithm performance based on real-world business requirements.

  • Code Excellence: Write exceptionally clean, testable, and debuggable code. You will be a champion for documentation and software development best practices within the ML lifecycle.

What you will need to be successful:

  • Bachelor’s or Master’s in Software Engineering, Computer Science, or equivalent.

  • 5-8+ years of experience in software engineering, with a significant focus on the deployment and maintenance of Machine Learning systems

  • Advanced proficiency in Python and Object-Oriented Programming (OOP) is non-negotiable.

  • Strong experience in AWS environments (Lambdas, SageMaker, Glue Tables, SQS/SNS, API Gateway, CloudWatch) and navigating IAM roles for secure deployments.

  • Expert-level familiarity with pytest and unit testing frameworks to ensure code reliability.

  • Deep knowledge of Linux environments and a natural instinct to automate repetitive tasks and workflows.

  • A strong understanding of ML model deployment patterns and current LLM architectures.

  • Ability to effectively communicate complex engineering concepts to colleagues with diverse technical backgrounds.

  • A proactive teammate who acts as a "resource person" for others, sharing knowledge and troubleshooting model issues effectively.

Language Requirements
French-English bilingualism is required.
In addition to fluency in French, successful candidates must have full professional proficiency in English in order to support and collaborate with English-speaking clients, colleagues and/or various stakeholders.

Annual Base Salary Range or Hourly Base Pay Range:

$111,308.33 - $155,435.00

Compensation Type:

Salary

Incentive Eligible:

Yes

Sales Commission Eligible:

No

Disclaimer: We strive to provide competitive compensation for this position, tailored to a variety of factors. The actual compensation will depend on elements such as seniority, merit, geographic location, education, experience,  travel requirements, and union designation.   Our compensation range is generally based on the national average for the country.  Additionally, benefits may vary depending on the region, business alignment, union involvement, and employee status.

We offer competitive compensation and comprehensive benefits and programs. We are an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, age, marital status, disability, status as a protected veteran, or any legally protected status.


What Trane Technologies employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Trane Technologies logo

About Trane Technologies

Sourced by ZipRecruiter

At Trane Technologies and through our businesses including Trane® and Thermo King®, we create innovative climate solutions for buildings, homes, and transportation that challenge what's possible for a sustainable world. We're a team that dares to look at the world's challenges and see impactful possibilities. We believe in a better future when we uplift others and enable our people to thrive at work and at home. We boldly go.

Industry

Industrial machinery manufacturing and machinery manufacturing

Company size

10,000+ Employees

Headquarters location

Davidson, NC, US