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Trane Technologies

Gestionnaire ML Ops / Manager ML Ops

Posted 3 Days Ago
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In-Office
Montréal, QC, CAN
Expert/Leader
In-Office
Montréal, QC, CAN
Expert/Leader
Lead and mentor a cross-functional ML Ops team to deploy, scale, and monitor ML/LLM models in production. Design AWS-based infrastructure and microservices using Terraform and managed AWS services, implement model monitoring for drift and performance, enforce software engineering best practices, and collaborate with researchers to transition experimental models to robust production systems.
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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 :

  • Leadership et mentorat d’équipe : Gérer une équipe interfonctionnelle de développeurs et d’AQ. Agir comme principale ressource technique pour le déploiement des modèles d’AA et encadrer les membres de l’équipe afin d’élever leurs pratiques d’ingénierie.

  • Déploiement en production : Surmonter les défis d’ingénierie liés au déploiement de modèles à grande échelle. Collaborer étroitement avec les chercheurs en AA pour faire passer les modèles du stade expérimental à des environnements de production robustes.

  • Conception d’infrastructures et de cadres : Diriger la conception et la mise en œuvre de cadres d’IA évolutifs. Utiliser les services gérés AWS (SageMaker, Lambda, tables Glue, files SQS/SNS, API Gateway) pour bâtir des microservices résilients.

  • Surveillance et santé des modèles : Déployer et maintenir des systèmes sophistiqués de surveillance du rendement des modèles. Détecter la dérive des données et des concepts, et suivre la diminution de performance afin d’assurer la fiabilité.

  • Innovation collaborative : Repérer et interpréter les tendances dans des ensembles de données complexes afin d’améliorer les algorithmes selon l’évolution des besoins d’affaires.

  • Qualité et documentation : Appliquer les meilleures pratiques de développement logiciel. Rédiger du code testable et débogable et maintenir une documentation complète des processus et procédures.

Ce dont vous aurez besoin pour réussir :

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

  • Plus de 10 ans d’expérience en génie logiciel ou dans un domaine connexe, avec une expérience démontrée de leadership technique.

  • Expérience approfondie avec Python et la programmation orientée objet (POO).

  • Expertise poussée en infrastructure AWS, Terraform, lacs de données, débogage via CloudWatch, gestion des rôles IAM et utilisation des services gérés AWS.

  • Connaissance essentielle de Linux et passion pour l’automatisation des tâches répétitives.

  • Maîtrise de Git et des tests unitaires rigoureux avec pytest.

  • Familiarité avec l’architecture des LLM et les meilleures pratiques de déploiement des grands modèles de langage.

  • Excellentes aptitudes de communication écrite et verbale, avec capacité de vulgariser des enjeux techniques complexes auprès de collègues aux parcours variés.

  • Capacité à penser différemment afin d’aligner les améliorations algorithmiques techniques sur les exigences d’affaires fondamentales.
     

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:

  • Team Leadership & Mentorship: Manage a cross-functional team of developers and QA. Act as the primary technical resource for ML model deployment and mentor team members to elevate their engineering practices.

  • Production Deployment: Navigate the engineering hurdles of deploying models at scale. Work closely with ML researchers to transition models from experimental stages to robust production environments.

  • Infrastructure & Framework Design: Lead the design and implementation of scalable AI frameworks. Utilize AWS managed services (SageMaker, Lambdas, Glue tables, SQS/SNS Queues, API Gateway) to build resilient microservices.

  • Model Monitoring & Health: Deploy and maintain sophisticated systems to monitor model performance. You will be responsible for detecting data and concept drift and tracking declining performance to ensure reliability.

  • Collaborative Innovation: Identify and interpret trends in complex datasets to enhance algorithms based on evolving business needs.

  • Quality & Documentation: Enforce software development best practices. Write testable, debuggable code and maintain comprehensive documentation of all work processes and procedures.

What you will need to be successful:

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

  • 10+ years of experience in software engineering or a related field, with a proven track record of leading technical teams.

  • Extensive experience with Python and Object-Oriented Programming (OOP).

  • Deep expertise in AWS infrastructure, terraform, data lake infrastructure, and specifically debugging via CloudWatch, managing IAM Roles, and utilizing AWS managed services.

  • Kknowledge of Linux and a passion for automating repetitive tasks.

  • Proficiency with Git and rigorous unit testing using Pytest.

  • AI/LLM Knowledge: Familiarity with LLM architecture and the best practices associated with deploying Large Language Models.

  • Communication: Exceptional written and verbal communication skills. You must be able to translate complex technical hurdles to co-workers with varied backgrounds.

  • Innovative Mindset: An ability to think outside the box to align technical algorithm enhancements with core business requirements.

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:

$131,036.66 - $183,504.99

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.

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