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Ai Platform Engineer Jobs in Quebec (NOW HIRING)

Platform Engineer

Montreal, QC

CA$100K - CA$160K/yr

Qualifications & Skills: * 4 to 7 years of experience as a DevOps/SRE/Platform engineer * Extensive ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Experience with SQL and distributed data platforms (Spark, Databricks, or Snowflake). GOOD TO HAVE * Azure AI-102, AWS ML Specialty, or Google Professional ML Engineer certification. * Exposure to ...

We are seeking a Senior Cloud Platform Engineer to join our Central Technology Build Engineering ... Innovate with emerging build technologies, cloud and AI What You'll Bring: * Fundamental ...

Working closely with the AI Platform ProductManagement team, they will be the key technical owner ... Lead the engineering effort to integrate AI models into the SIMPRO core platform with velocity ...

Work collaboratively with AI teams, Developers and business units for platform on-boarding and enablement * Apply DevOps best practices to continuously improve the platform's performance, stability ...

This requires a data and AI platform that ingests, resolves, scores, decides, and acts in minutes ... Translate architecture into staffed delivery with each engineering team; collaborate with clinical ...

Shop Builder is Xsolla's storefront platform - used by publishers and game developers to launch and operate game shops, from straightforward catalog and webshops to fully custom storefronts built ...

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Ai Platform Engineer information

See Quebec salary details

$41K

$134.9K

$195K

How much do ai platform engineer jobs pay per year?

As of Jul 27, 2026, the average yearly pay for ai platform engineer in Quebec is $134,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $157,500.00 per year, depending on experience, location, and employer.

Which 3 jobs will survive AI?

AI Platform Engineers are likely to continue to be in demand as they develop, deploy, and maintain AI systems, requiring skills in machine learning, cloud computing, and programming. Jobs that involve complex problem-solving, creativity, and emotional intelligence—such as healthcare professionals, educators, and skilled trades—are also expected to persist despite AI advancements. These roles often require human judgment and interpersonal skills that AI cannot easily replicate.

What are AI Platform Engineers?

AI Platform Engineers are technology professionals who design, build, and maintain the infrastructure that supports the development, deployment, and scaling of artificial intelligence (AI) and machine learning (ML) models. They work closely with data scientists and software engineers to ensure that AI solutions can run efficiently and securely in production environments. Their responsibilities often include managing cloud or on-premises platforms, automating workflows, and implementing best practices for model versioning, monitoring, and resource optimization.

How does an AI Platform Engineer typically collaborate with data scientists and software engineers in a project environment?

AI Platform Engineers often serve as a bridge between data scientists and software engineers, ensuring that machine learning models are seamlessly integrated into scalable, production-ready systems. They work closely with data scientists to understand model requirements and deployment needs, and with software engineers to embed these models within applications and services. This collaboration involves frequent communication, joint troubleshooting, and participation in code reviews to maintain a robust and efficient AI infrastructure.

What does an AI platform engineer do?

An AI platform engineer designs, develops, and maintains the infrastructure and tools needed to deploy and manage artificial intelligence models at scale. They work with cloud services, programming languages, and machine learning frameworks to ensure efficient model deployment, monitoring, and optimization in production environments.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as an AI Platform Engineer or senior AI researcher, that offers a total compensation package including salary, bonuses, and stock options. These roles often require advanced skills in machine learning, deep learning, cloud platforms, and extensive experience, and are usually found in leading tech companies or AI-focused organizations.

What engineer makes $500,000 a year?

Senior AI Platform Engineers or Machine Learning Engineers with extensive experience, advanced skills in cloud computing, and expertise in AI tools can earn salaries around or above $500,000 annually, especially in high-demand industries or companies. Such roles often require strong programming, data management, and system architecture knowledge, along with relevant certifications and a track record of successful projects.

What is the difference between Ai Platform Engineer vs Data Engineer?

AspectAi Platform EngineerData Engineer
CredentialsBachelor's in CS, AI, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentDeveloping AI infrastructure, deploying ML models, working with cloud servicesBuilding data pipelines, managing data storage, ensuring data quality
Industry UsageTech companies, AI startups, cloud providersFinance, healthcare, e-commerce, any data-driven industry

While both roles involve working with data and cloud platforms, Ai Platform Engineers focus on building and maintaining AI infrastructure and deploying machine learning models. Data Engineers primarily develop data pipelines and manage data storage. The roles often collaborate but serve different core functions within AI and data ecosystems.

What are the key skills and qualifications needed to thrive as an AI Platform Engineer, and why are they important?

To thrive as an AI Platform Engineer, you need strong programming skills (especially in Python and Java), a background in computer science or related fields, and experience with machine learning frameworks. Familiarity with cloud platforms (like AWS, Azure, or GCP), containerization tools (Docker, Kubernetes), and CI/CD systems is typically required, along with certifications such as Google Cloud Professional Machine Learning Engineer. Excellent problem-solving, collaboration, and communication skills help you integrate AI solutions across teams and projects. These competencies ensure the efficient development, deployment, and maintenance of scalable AI systems in dynamic production environments.
What are popular job titles related to Ai Platform Engineer jobs in Quebec? For Ai Platform Engineer jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Ai Platform Engineer jobs in Quebec look for? The top searched job categories for Ai Platform Engineer jobs in Quebec are:
Infographic showing various Ai Platform Engineer job openings in Quebec as of July 2026, with employment types broken down into 71% Full Time, 20% Part Time, and 9% Contract. Highlights an 63% Physical, 3% Hybrid, and 34% Remote job distribution, with an average salary of $134,857 per year, or $64.8 per hour.

Ingenieur plateforme IA / AI Platform Engineer

LANDR

Montreal, QC • On-site

Full-time

Posted 9 days ago


Job description

LANDR est une societe audio a croissance rapide composee de creatif.ve.s, de technologues, de professionnel.le.s de la musique ainsi que de toutes les combinaisons possibles de ces domaines. Ensemble, nous revolutionnons le processus des createur.trice.s de musique pour les aider a creer, maitriser, distribuer et promouvoir leur musique.


Nous aimons la musique. Nous aimons les musiciens. Notre mission est de donner aux createurs et aux creatrices de musique la liberte de creer et d'etre entendus. Nous apportons chaque jour notre amour de la musique au bureau et nous innovons continuellement pour creer des experiences qui ravissent et engagent notre public de plus de 6 millions de createurs de musique. Nous aimons les meilleures pratiques, mais nous n'avons pas peur de les briser.


L'opportunite


Nous reinventons la maniere dont les createurs de musique interagissent avec LANDR grace a l'IA conversationnelle.

La creation et la distribution musicales sont complexes. Aujourd'hui, les createurs doivent naviguer parmi des dizaines de menus, d'outils et de flux de travail pour accomplir des taches simples. Nous pensons qu'il existe une meilleure solution.


Vous serez l'architecte de cette intelligence. Vous concevrez un ecosysteme collaboratif d'agents IA capables de reflechir a l'intention de l'utilisateur, de valider les donnees par rapport a des regles externes strictes et de resoudre les problemes de maniere proactive avant qu'ils ne surviennent.


Responsabilites

  • Architecture agentique - Concevoir et mettre en uvre la logique d'interaction pour un ecosysteme multi-agents ou des agents distincts collaborent pour creer une source unique et verifiable de verite.
  • Architecture des donnees - Concevoir et creer des pipelines qui permettent aux systemes d'IA d'interroger instantanement les catalogues d'utilisateurs, les metadonnees de publication, l'historique de maitrise, les statistiques d'engagement et le comportement de la plateforme.
  • Optimisation des pipelines - Gerer l'acces aux donnees en temps reel a grande echelle. Lorsque 10 000 utilisateurs communiquent simultanement, la recuperation du contexte ne doit pas constituer un goulot d'etranglement.
  • Conception d'API - Creer des interfaces propres et rapides qui permettent a notre orchestrateur IA d'acceder au contexte utilisateur sans toucher directement aux bases de donnees de production.
  • Optimisation du systeme - Equilibrer l'utilisation de LLM couteux avec une logique deterministe afin d'optimiser les couts et la latence a grande echelle.
  • Collaboration sur les produits - travaillez avec le responsable des produits IA et les developpeurs full-stack pour traduire une logique backend complexe en une experience utilisateur conversationnelle et fluide.
  • Barrieres de securite et surete - mettez en place des couches de validation strictes pour eviter les hallucinations sur les regles de conformite critiques et les politiques externes, et garantir que les donnees des utilisateurs sont traitees en toute securite, avec des limites claires sur ce a quoi l'IA peut acceder et comment nous l'utilisons.


Qualifications

  • Cadres agentifs - Experience averee dans la creation de systemes agentifs de niveau production (LangChain, AutoGPT ou orchestrateurs personnalises).
  • Experience pratique des modeles contextuels LLM - Vous avez travaille sur des systemes RAG, des fenetres contextuelles ou des produits d'IA qui necessitent un acces personnalise aux donnees.
  • Solides bases en matiere de donnees - Maitrise de Python, SQL et des modeles ETL pour structurer les donnees en vue de leur recuperation par l'IA.
  • Experience avec les bases de donnees vectorielles et la recherche semantique - Vous comprenez les integrations, la recherche par similarite et la maniere de structurer les donnees pour la recuperation par l'IA (Pinecone, Weaviate, Qdrant ou similaire).
  • Evaluation LLM - Experience dans la mise en place de workflows LLM-as-a-judge ou human-in-the-loop pour mesurer la precision.


Atouts:

  • Connaissances fondamentales en apprentissage automatique (ML) - vous comprenez l'apprentissage supervise et non supervise, vous etes capable d'evaluer les compromis lies au choix des modeles et vous appliquez cette perspective aux decisions relatives a l'infrastructure.


Voici quelques avantages offerts chez LANDR:

  • Une remuneration competitive, basee sur votre role, votre experience et votre expertise
  • Couverture d'assurance maladie, avec acces a un medecin via Maple et a un programme d'aide aux employes (via PeopleConnect)
  • Acces a notre programme de REER, incluant une contribution de l'employeur equivalant jusqu'a 2% de votre salaire annuel
  • Evenements de bureau et sociaux frequents (traiteur le lundi, bagel le mardi, 5@7, etc.)
  • Votre anniversaire est un jour de conge
  • Allocation annuelle pour le transport en commun (employes de Montreal) et pour activites sportives
  • Acces gratuit a notre studio de musique (pour pratiquer ou enregistrer)
  • Acces gratuit aux produits LANDR et Reason
  • Espace de bureau ouvert au Centre-Ville a proximite de la station de metro Square-Victoria
  • Groupe de musique LANDR
  • Partenariats avec des evenements et festivals musicaux locaux (MUTEK, Pop Montreal, Igloofest...)


Chez LANDR, non seulement nous acceptons la diversite, mais nous la celebrons, nous la soutenons, et nous prosperons dans l'interet de nos employe.e.s, de nos produits et de notre communaute. LANDR s'efforce chaque jour de creer un lieu de travail plus diversifie. Nous encourageons vivement les personnes de couleur, les femmes, les personnes LGBTQ, les personnes de toutes religions, de tous les ages et de toutes les communautes marginalisees a postuler.


Nous acceptons les gens tels qu'ils sont et croyons fermement que la diversite est essentielle a notre succes! Si vous postulez chez LANDR, c'est parce que vous souhaitez contribuer a notre succes et a notre culture extraordinaire, et nous en sommes reconnaissants!


Nous travaillons fort pour creer la meilleure experience pour nos employe.e.s et nous aimerions que vous y joignez!

-------------


LANDR is a fast-growing audio company made up of left-brained creative technologists, right-brained music professionals and everyone in between. Together, we are revolutionizing the process for music makers to help them create, master, distribute and promote their music.


We love music. We love musicians. Our mission is to give music makers the freedom to create and be heard. We bring our love of music to the office every day and we are continuously innovating to create experiences that delight and engage our audience of over 6 million music creators.


The Opportunity

We're reimagining how music creators interact with LANDR using conversational AI.


Music creation and distribution are complex. Creators today navigate dozens of menus, tools, and workflows just to accomplish simple goals. We believe there's a better way.


You will be the architect of this intelligence. You will design a collaborative ecosystem of AI agents that can "think" about user intent, validate data against strict external rules, and proactively solve problems before they occur.


Responsibilities

  • Agentic Architecture - Architect and implement the interaction logic for a multi-agent ecosystem where distinct agents collaborate to build a single, verifiable source of truth.
  • Data Architecture - Design and build pipelines that make user catalogs, release metadata, mastering history, engagement stats, and platform behavior instantly queryable by AI systems
  • Pipeline Optimization - Handle real-time data access at scale. When 10,000 users are talking simultaneously, context retrieval can't be the bottleneck.
  • API Design - Build clean, fast interfaces that let our AI orchestrator access user context without touching production databases directly
  • System Optimization - Balance the use of expensive LLMs with deterministic logic to optimize for cost and latency at scale.
  • Product Collaboration - Work with AI Product owner and full-stack developers to translate complex backend logic into a seamless, conversational user experience.
  • Guardrails & Safety - Implement strict validation layers to prevent hallucinations on critical compliance rules and external policies as well as ensure user data is handled securely, with clear boundaries around what AI can access and how we use it.


Qualifications

  • Agentic Frameworks - Proven experience building production-grade agentic systems (LangChain, AutoGPT, or custom orchestrators).
  • Hands-on experience with LLM context patterns - You've worked on RAG systems, context windows, or AI products that require personalized data access
  • Strong Data Foundation - Proficiency in Python, SQL, and ETL patterns to structure data for AI retrieval.
  • Experience with vector databases and semantic search - You understand embeddings, similarity search, and how to structure data for AI retrieval (Pinecone, Weaviate, Qdrant, or similar)
  • LLM Evaluation - Experience setting up "LLM-as-a-judge" or human-in-the-loop workflows to measure accuracy.


Nice to have

  • Foundational ML knowledge - You understand supervised and unsupervised learning, can reason about model selection tradeoffs, and bring that lens to infrastructure decisions


Here are a few perks that we enjoy at LANDR:

  • Competitive compensation, based on your role, experience and expertise
  • Health insurance coverage, with access to a doctor via Maple and to an Employee Assistance Program (via PeopleConnect)
  • RRSP program, including an employer matching contribution of up to 2% of your annual salary
  • Frequent office and social events (Catering on Monday, Bagel Tuesdays, 5@7, etc.)
  • Your birthday is a free day
  • Annual public transit (Montreal employees) & sport activity allowance
  • Free access to our music studio (for practice or recording)
  • Free access to LANDR and Reason products
  • Open office space in Downtown close to Square-Victoria Metro Station
  • LANDR Band
  • Partnerships with local music events & festivals (MUTEK, Pop Montreal, Igloofest...)


Our Commitment to Diversity

At LANDR, we don't just accept diversity, we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products, and our community. LANDR is striving every day to create a more diverse workplace, and we strongly encourage applications from people of color, women, LGBTQ people, people of any religion, age, or belonging to any marginalized community.


We accept people as they are and firmly believe diversity is essential to our success! If you're applying to LANDR, it's because you want to contribute to our amazing company and culture, and we're thankful for that!


We work hard to create the best experience for our employees and we'd love for you to be a part of it!