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Added 32 mins ago
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Artificial Intelligence Consultant
SMARTFOX
Canada
- Full-time
Work with data engineers and developers to connect solutions to client systems, data pipelines, and APIs
Added 32 mins ago
TV
Technical Business Development Director
TandemLaunch Ventures Studio & Funds
Montreal, QC
- Full-time
…hardware-enabled technologies, machine learning, and embedded systems, working directly with researchers from major university labs. We are one of very few venture studios globally with 15+…
Added 32 mins ago
TV
Director of Product Strategy and Commercialization
TandemLaunch Ventures Studio & Funds
Montreal, QC
- Full-time
…hardware-enabled technologies, machine learning, and embedded systems, working directly with researchers from major university labs. We are one of very few venture studios globally with 15+…
Added 48 mins ago
Directeur de la stratégie produit et de la commercialisation | Director of Product Strategy and Commercialization
TandemLaunch
Montreal, QC
Added 1 hour ago
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GenAI Prompt Engineer
TechDoQuest
Toronto, ON
- Contract
-Prompt Writing: Design and refine creative, effective, and contextually relevant prompts for generative AI systems to maximize performance and accuracy across various use cases.
Added 1 hour ago
GU
AI Agentic Systems & Automation Engineer
GenCore Utilities Ltd.
Markham, ON
- $100,000 to $140,000 CAD / year
- Full-time
GenCore Utilities Ltd. is seeking an AI Agentic Systems & Automation Engineer to design, build, and deploy AI solutions that improve engineering, operations, project delivery, and business…
Added 2 hours ago
Agentic AI Architect, Kitchener, ON ( Hybrid)
Siemens
Kitchener, ON
…technical design of our Agentic AI platform and ensure the agent systems we build are coherent, scalable, and production-ready. The role focuses on architecture and system design -…
Added 2 hours ago
CL
Senior Cloud DevOps Engineer
Charger Logistics Inc
Brampton, ON
- Full-time
The Senior Cloud DevOps Engineer will design and implement enterprise-scale cloud infrastructure, drive automation strategies, and mentor engineering teams while architecting…
Added 2 hours ago
CL
Senior Cloud DevOps Engineer
Charger Logistics Inc.
Brampton, ON
- Full-time
The Senior Cloud DevOps Engineer will design and implement enterprise-scale cloud infrastructure, drive automation strategies, and mentor engineering teams while architecting…
Added 3 hours ago
SA
Staff Software Engineer, Teleoperation
Sanctuary AI
Vancouver, BC
- Full-time
Sanctuary AI is hiring a Staff Software Engineer to drive and evolve the production teleoperation and data collection software that enables robot operators to control robots.
Added 4 hours ago
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Senior Python Engineer
Citi
Mississauga, ON
- Full-time
Hands-on experience with CI/CD systems (Jenkins, GitLab CI, GitHub Actions, Bitbucket Pipelines) for automated deployment.
Added 4 hours ago
VC
Staff Software Engineer
Valsoft Corporation
Remote, Canada
- Full-time
- Remote
We're hiring a Staff Software Engineer to own architecture and design decisions for our platform, including the modernization of legacy enterprise systems into modern, cloud-capable…
Added 4 hours ago
WT
Data Engineer
Wissen Technology
Montreal, QC
- Full-time
We are looking for a Data Engineer with strong backend engineering fundamentals and hands‑on experience building scalable, high‑performance data pipelines. The ideal candidate comes from a…
Added 4 hours ago
VT
AI Platform Developer
Volgo Technologies
Toronto, ON
- Contract
We are looking for a hands-on engineer who can build and deploy production-grade Agentic AI and multi-agent systems using Google ADK and MCP, while developing scalable AI platform…
Added 5 hours ago
Staff Data Engineer
ExaCare AI
Toronto, Ontario
We’re looking for a Staff Data Engineer who thrives in an environment with strong ownership and can drive complex data initiatives from concept to production. You’ll build the pipelines,…
Added 5 hours ago
Product Security Engineer
Asana
Vancouver, BC
We're looking for a Product Security Engineer to join our Product Security team in Vancouver. You'll be a key member of our security engineering team, partnering directly with product and…
Added 5 hours ago
F
Technical Consultant (Data & AI)
Fastloop
Vancouver, BC
- Full-time
You aren’t just a “Data Engineer” or a “Software Engineer”; you are the “connective tissue” of modern intelligence. You will be responsible for the programmatic development of Agentic…
Added 5 hours ago
Staff Software Engineer
Lantern
Vancouver, BC
As a Staff Engineer, you’ll partner with cross-functional teams – including engineering leads, product managers, clinicians, and compliance – to influence the design and delivery of…
Added 5 hours ago
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Data Quality Engineer
Hays
Toronto, ON
- Contract
A leading organization is seeking a highly skilled and experienced Senior Quality Engineer to join its Enterprise Technology and Data team.
Added 5 hours ago
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Staff Software Engineer
Lantern
Vancouver, BC
- Full-time
As a Staff Engineer, you’ll partner with cross-functional teams – including engineering leads, product managers, clinicians, and compliance – to influence the design and delivery of…
Added 6 hours ago
TC
Forward deployed Engineer
Tata Consultancy Services
Toronto, ON · Greater Toronto Area, Canada
- $100,000 to $120,000 CAD / year
- Full-time
Bachelor’s degree in computer science, Engineering, Information Systems, Data Management, or a related discipline.
Added 6 hours ago
TC
Forward deployed Engineer
Tata Consultancy Services
Toronto, ON
- $100,000 to $120,000 CAD / year
- Full-time
Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline.
Added 6 hours ago
ZS
Forward Deployed Engineer
Zodiac Solutions, Inc
Toronto, ON
- Full-time
Bachelor’s degree in computer science, Engineering, Information Systems, Data Management, or a related discipline.
Added 6 hours ago
TD
Robotics QA Automation Engineer
TELUS Digital
Canada
- Full-time
Integrate orchestration platforms with cloud environments and enterprise systems.
Added 11 hours ago
A
Principal Engineer - Open Source Data Platform (ODP)
Acceldata
Kitchener, ON
- Full-time
We are seeking a Principal Engineer with at least 14 years of experience to serve as a technical visionary and thought leader for Acceldata's Open Data Platform (ODP). In this role, you…

Yeji Data Lab

Senior Machine Learning Engineer (Consulting)

Greater Montreal Metropolitan Area, QC, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Nov 7, 2026
Posting language: English · French
Posted: Oct 8, 2026

Original job description

English section of this bilingual listing.

About Us

As a global boutique firm, we partner with leading organizations to solve their most pressing challenges through Machine Learning and data engineering, creating sustainable value at scale. As a client-facing consultancy, our team must be adaptable, technically rigorous, and capable of designing systems from the ground up across a wide range of industries in North America and beyond.

Role Overview

We are looking for a Senior Machine Learning Engineer to design, build, and deploy scalable ML solutions for our clients. You will work across diverse projects, collaborating with cross-functional teams to deliver production-ready AI systems in modern cloud environments.

Key Responsibilities

Design, build, and deploy machine learning and deep learning models in production environments
Develop and maintain MLOps pipelines (CI/CD, monitoring, model versioning) across cloud platforms
Work with large-scale datasets for training, validation, and evaluation
Implement and optimize LLM-based solutions, including:
Fine-tuning foundation models
Building and deploying RAG (Retrieval-Augmented Generation) systems
Collaborate with clients and internal teams to translate business problems into ML solutions
Ensure model performance, scalability, and reliability in production
Stay current with advancements in AI/ML, especially in generative AI and LLMs

Required Qualifications

4+ years of experience in Machine Learning Engineering or related roles
Strong experience with Python and ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn)
Apply and optimize traditional machine learning algorithms (e.g., tree-based models, gradient boosting, neural networks) for structured data problems
Hands-on experience with deep learning models (e.g., CNNs, RNNs)
Experience building and deploying production ML systems
Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow, CI/CD pipelines)
Experience with cloud platforms (at least one of AWS, Azure, or GCP; multi-cloud is a plus)
Implement and optimize LLM-based solutions, including: Fine-tuning foundation models, prompt engineering, building and deploying RAG (Retrieval-Augmented Generation) systems
Experience building RAG pipelines (vector databases, embeddings, retrieval strategies)

Nice to Have

Experience in a consulting or client-facing role
Familiarity with tools like LangChain, LlamaIndex, or similar frameworks
Knowledge of data engineering (Spark, SQL, data pipelines)
Experience with containerization and orchestration (Docker, Kubernetes)
Understanding of model governance, monitoring, and responsible AI

What We Offer

Opportunity to work on cutting-edge AI/ML and GenAI projects
Exposure to a variety of industries and problem domains
Flexible work environment (hybrid)
Competitive compensation and growth opportunities

Français

À propos de nous

Read the full bilingual original

About Us

Role Overview

Key Responsibilities

Design, build, and deploy machine learning and deep learning models in production environments
Develop and maintain MLOps pipelines (CI/CD, monitoring, model versioning) across cloud platforms
Work with large-scale datasets for training, validation, and evaluation
Implement and optimize LLM-based solutions, including:

Fine-tuning foundation models

Building and deploying RAG (Retrieval-Augmented Generation) systems

Collaborate with clients and internal teams to translate business problems into ML solutions
Ensure model performance, scalability, and reliability in production
Stay current with advancements in AI/ML, especially in generative AI and LLMs

Required Qualifications

4+ years of experience in Machine Learning Engineering or related roles
Strong experience with Python and ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn)
Apply and optimize traditional machine learning algorithms (e.g., tree-based models, gradient boosting, neural networks) for structured data problems
Hands-on experience with deep learning models (e.g., CNNs, RNNs)
Experience building and deploying production ML systems
Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow, CI/CD pipelines)
Experience with cloud platforms (at least one of AWS, Azure, or GCP; multi-cloud is a plus)
Implement and optimize LLM-based solutions, including: Fine-tuning foundation models, prompt engineering, building and deploying RAG (Retrieval-Augmented Generation) systems
Experience building RAG pipelines (vector databases, embeddings, retrieval strategies)

Nice to Have

Experience in a consulting or client-facing role
Familiarity with tools like LangChain, LlamaIndex, or similar frameworks
Knowledge of data engineering (Spark, SQL, data pipelines)
Experience with containerization and orchestration (Docker, Kubernetes)
Understanding of model governance, monitoring, and responsible AI

What We Offer

Opportunity to work on cutting-edge AI/ML and GenAI projects
Exposure to a variety of industries and problem domains
Flexible work environment (hybrid)
Competitive compensation and growth opportunities

Français

À propos de nous

En tant que boutique d’envergure internationale, nous collaborons avec des organisations de premier plan pour relever leurs défis les plus stratégiques grâce au Machine Learning et à l’ingénierie des données, afin de créer une valeur durable. En tant que firme-conseil en contact direct avec les clients, notre équipe doit faire preuve d’adaptabilité, de rigueur technique et d’une forte capacité à concevoir des systèmes de bout en bout pour divers secteurs d’activité en Amérique du Nord et ailleurs.

Aperçu du poste

Nous recherchons un ingénieur sénior en apprentissage automatique pour concevoir, développer et déployer des solutions d’IA évolutives pour nos clients. Vous travaillerez sur des projets variés, en collaboration avec des équipes multidisciplinaires, afin de livrer des systèmes d’IA prêts pour la production dans des environnements cloud modernes.

Principales responsabilités

Concevoir, développer et déployer des modèles de machine learning et de deep learning dans des environnements de production
Développer et maintenir des pipelines MLOps (CI/CD, surveillance, gestion des versions des modèles) sur des plateformes cloud
Travailler avec des jeux de données à grande échelle pour l’entraînement, la validation et l’évaluation
Mettre en œuvre et optimiser des solutions basées sur les LLM, notamment :
l’ajustement fin de modèles de fondation
la conception et le déploiement de systèmes RAG (Retrieval-Augmented Generation)
Collaborer avec les clients et les équipes internes afin de traduire des enjeux d’affaires en solutions de machine learning
Garantir la performance, l’évolutivité et la fiabilité des modèles en production
Se tenir à jour sur les avancées en IA/ML, en particulier en IA générative et en LLM

Qualifications requises

4 ans ou plus d’expérience en ingénierie du machine learning ou dans des rôles connexes
Solide expérience avec Python et les frameworks de ML (p. ex. PyTorch, TensorFlow, Scikit-learn)
Capacité à appliquer et à optimiser des algorithmes traditionnels de machine learning (p. ex. modèles arborescents, gradient boosting, réseaux neuronaux) pour des problèmes sur données structurées
Expérience pratique avec des modèles de deep learning (p. ex. CNN, RNN)
Expérience dans la conception et le déploiement de systèmes de ML en production
Maîtrise des pratiques et outils MLOps (p. ex. MLflow, Kubeflow, Airflow, pipelines CI/CD)
Expérience avec des plateformes cloud (au moins une parmi AWS, Azure ou GCP; le multi-cloud est un atout)
Expérience dans la mise en œuvre et l’optimisation de solutions basées sur les LLM, notamment : l’ajustement fin de modèles de fondation, le prompt engineering, la conception et le déploiement de systèmes RAG (Retrieval-Augmented Generation)
Expérience dans la conception de pipelines RAG (bases de données vectorielles, embeddings, stratégies de récupération)

Atouts supplémentaires

Expérience en cabinet de conseil ou dans un rôle en contact direct avec la clientèle
Familiarité avec des outils comme LangChain, LlamaIndex ou des frameworks similaires
Connaissance de l’ingénierie des données (Spark, SQL, pipelines de données)
Expérience en conteneurisation et orchestration (Docker, Kubernetes)
Compréhension de la gouvernance des modèles, de leur surveillance et de l’IA responsable

Ce que nous offrons

L’occasion de travailler sur des projets de pointe en IA/ML et en IA générative
Une exposition à une grande variété de secteurs et de problématiques
Un environnement de travail flexible (hybride)
Une rémunération concurrentielle et des possibilités d’évolution professionnelle

Apply About employer

More about this job

Responsibilities

Design, build, and deploy production-ready machine learning and deep learning systems, including scalable LLM and RAG solutions. Develop and maintain cloud-based MLOps pipelines, collaborate with clients and internal teams to translate business needs into ML solutions, and ensure production systems are reliable and performant.

Requirements

Requires at least four years of experience in machine learning engineering or a related role, strong Python and ML framework skills, and experience deploying production ML systems. Candidates should also have hands-on deep learning, MLOps, cloud, LLM fine-tuning, prompt engineering, and RAG pipeline experience.

Skills

Python
PyTorch
TensorFlow
Scikit-Learn
Traditional Machine Learning
Deep Learning
MLOps
CI/CD
Cloud Platforms
Large Language Models
Fine-Tuning
Prompt Engineering
Retrieval-Augmented Generation
Vector Databases
Embeddings
Model Monitoring

Benefits

Flexible Work Environment
Competitive Compensation
Growth Opportunities

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Deep Learning
Python
PyTorch
TensorFlow
Scikit-Learn
Tree-Based Models
Gradient Boosting
Neural Networks
CNNs
RNNs
MLOps
MLflow
Kubeflow
Airflow
CI/CD
AWS
Azure
GCP
Large Language Models
Foundation Model Fine-Tuning
Prompt Engineering
Retrieval-Augmented Generation
Vector Databases
Embeddings
LangChain
LlamaIndex
Spark
SQL
Docker

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