Trane Technologies

Développeur en apprentissage automatique III / Machine Learning Developer III

Trane Technologies$111K — $155K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's in Software Engineering, Computer Science, or equivalent
  • 5-8+ years of experience in software engineering, focused on Machine Learning systems deployment and maintenance
  • Advanced proficiency in Python and Object-Oriented Programming (OOP)
  • Strong experience with AWS environments and IAM role management
  • Expert-level familiarity with pytest and unit testing frameworks
  • Deep knowledge of Linux environments and automation
  • Understanding of ML model deployment patterns and current LLM architectures
  • Effective communication skills for conveying complex concepts to diverse technical audiences
  • Proactive team player offering support and knowledge sharing.

Responsibilities

  • Participate in designing and implementing scalable AI frameworks for ongoing and future projects
  • Collaborate with ML engineers and researchers for seamless model deployment
  • Develop systems to monitor performance decay and detect data/concept drift
  • Provide high-level technical support in AI programming to ensure project milestones are met
  • Evolve methodologies and develop new techniques across engineering and research initiatives
  • Analyze complex data patterns to enhance algorithm performance in real-world applications
  • Write clean, testable code and advocate for software development best practices.

Benefits

  • Dedicated in-office collaboration days each month for relationship building, learning, and innovation.
Full Job Description
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.

About Trane Technologies

Trane Technologies is a global climate innovator. Through our strategic brands Trane and Thermo King, and our portfolio of environmentally responsible products and services, we bring efficient and sustainable climate solutions to buildings, homes and transportation. Our innovative solutions have helped make buildings and homes comfortable, while more energy efficient and environmentally friendly. We also provide transport temperature control solutions that are used in the food, beverage and pharmaceutical sectors. Trane Technologies is committed to achieving carbon neutrality by 2030 and has been named to the Dow Jones Sustainability World Index for the tenth consecutive year.
Learn more about Trane Technologies
Size
37,000 employees
Market Cap
$39 billion
Industry
Net Income
$854.8 million
5 Year Trend
+0.9%
Revenue
$12.4 billion
NASDAQ

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