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Added 20 mins ago
GM
Senior Software Developer - Virtualization and SIL Integration
General Motors
Markham, ON
- Full-time
Work Arrangement: This opening is hybrid, the successful candidate is expected to report to the office - Markham Elevation Centre (MEC) three times per week, at minimum.
Added 45 mins ago
GC
Data Engineer
GEI Consultants, Inc.
Guelph, ON
- $90,000 to $150,000 CAD / year
- Full-time
The Data Engineer is responsible for designing, building, and maintaining the data pipelines and integrations that power GEI’s AI solutions and digital initiatives. This role focuses on…
Added 1 hour ago
G
CyberSecurity Specialist- Agentic AI
Galent
Toronto, ON · North York, ON
- Contract
Ideal Candidate: Security Researcher + Software Engineer with experience in academic/market research and emerging cybersecurity technology evaluation.
Added 1 hour ago
A
IAM Engineer with Python Developer Experience // Montreal, QC(Hybrid)//FTE
AceStack
Montreal, QC
- Full-time
Role: IAM Engineer with Python Developer Experience
Added 1 hour ago
RI
Senior Full Stack Engineer - Java /
Rose International
Mississauga, ON
- Full-time
Job Title: Senior Full Stack Engineer - Java / AI
Added 2 hours ago
YD
Senior Machine Learning Engineer (Consulting)
Yeji Data Lab
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
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…
Added 2 hours ago
GM
Senior Software Developer
General Motors
Markham, ON · Oshawa, ON
- Full-time
Hybrid - This role is categorized as hybrid. This means the successful candidate is expected to report to our hub in Markham, ON three times per week, at minimum.
Added 2 hours ago
Staff Photonics Design & PDK Modeling Engineer
Lightmatter
Toronto, ON
We are hiring a Photonics PDK Modeling Engineer to join our team. In this role, you will develop our internal Process Design Kit (PDK). You will act as the architect of our component…
Added 2 hours ago
TH
AI Engineer | Full time | AI Innovations
Trillium Health Partners
ON · ON, Canada
- Full-time
Reporting to the Director, AI & Digital Planning, the AI Engineer will be responsible for using the latest AI tools to design, prototype, build, evaluate, and scale AI solutions including…
Added 2 hours ago
RE
Data Architect
Rodan Energy Solutions Inc.
Mississauga, ON
- Full-time
Modern Data Stack: Work in Databricks (Unity Catalog, Delta Lake, serverless compute, Lakeflow Connect/Auto Loader, MLflow, Genie) with Python/PySpark and SQL, deployed via Asset Bundles.
Added 2 hours ago
L
Staff Photonics Design & PDK Modeling Engineer
Lightmatter
Toronto, ON
- Full-time
We are hiring a Photonics PDK Modeling Engineer to join our team. In this role, you will develop our internal Process Design Kit (PDK). You will act as the architect of our component…
Added 3 hours ago
RE
Data Architect
Rodan Energy Solutions Inc.
Mississauga, ON
- Full-time
Modern Data Stack: Work in Databricks (Unity Catalog, Delta Lake, serverless compute, Lakeflow Connect/Auto Loader, MLflow, Genie) with Python/PySpark and SQL, deployed via Asset Bundles.
Added 3 hours ago
G
DevOps- AI Platform Engineer
Galent
Halifax, NS
- Contract
An engineer mindset, SDLC experience with production class delivery, strong analytical mindset, communication skills, and sense of ownership / drive
Added 4 hours ago
EN
Senior Forward Deployed Engineer (10570) Toronto, Canada
Extreme Networks
Toronto, ON
- Full-time
As a Senior Forward Deployed Engineer, you will work directly with customer technical teams to design, build, deploy, and stabilize production solutions using Extreme's products and…
Added 4 hours ago
CO
Staff Software Engineer
Capital One
Toronto, ON
- Full-time
Find your rhythm: We believe trust fosters the flexibility and autonomy required to balance personal needs with a focus on high performance. We support a hybrid model – with 3 days in the…
Added 4 hours ago
A
Senior Verification Engineer - Security
Arm
Toronto, ON
- Full-time
As a creative problem solving Security and Embedded Processor Verification Engineer, you will be part of a team that will define and realize the Hardware Security IP and Subsystem. We will…
Added 5 hours ago
M
Network Engineer
Moneris
Toronto, ON
- Full-time
Moneris is seeking a highly skilled Network Engineer to design, implement, automate, and support the enterprise network infrastructure that powers our business and payment processing…
Added 5 hours ago
F
Senior Machine Learning Engineer
Fusemachines
Remote, Canada
- Contract
- Remote
You must possess a strong hybrid skill set: deep expertise in applied machine learning combined with production-grade software engineering skills. You will not just build models in…
Added 5 hours ago
Senior Backend Product Developer, SCM Tech Fulfillment
HelloFresh
Toronto, ON
…preparing for expansion, we are looking for a Senior Software Engineer with strong backend experience, a talent for turning complex logic into clean, reliable systems, and enough full-stack…
Added 5 hours ago
V
Forward Deployed Engineer - Full Stack AI Solutions
VistaVu
Calgary, AB
- Full-time
As a Forward Deployed Engineer - AI Solutions at VistaVu Solutions, you will work alongside customers to understand their business problems, learn how their teams operate, and build AI…
Added 5 hours ago
M
Technical Architect- AI
Mphasis
Toronto, ON
- Full-time
AI Frameworks & Development: LangChain, LangGraph, LlamaIndex, FastAPI, REST APIs, Python, SQL
Added 5 hours ago
P
JAMS Platform Engineer
ProwessSoft
Toronto, ON
- Contract
Engineer and administer JAMS Scheduler| including Scheduler| Agents| Executors| queues| resources and job configuration. Improve platform reliability| performance| capacity| resilience and…
Added 5 hours ago
VS
Forward Deployed Engineer - Full Stack AI Solutions
VistaVu Solutions
Calgary, AB
- Full-time
As a Forward Deployed Engineer - AI Solutions at VistaVu Solutions, you will work alongside customers to understand their business problems, learn how their teams operate, and build AI…
Added 5 hours ago
GD
Software Engineering Developer, DevOps
General Dynamics Missions System International
Calgary, AB · Ottawa, Ontario
- $85,000 to $110,000 CAD / year
- Full-time
We are seeking a skilled DevOps Engineer to join our team and enhance our development and operational efficiency. This role is ideal for someone who thrives in a cloud-agnostic environment…
Added 6 hours ago
AI
Machine Learning Engineer- AWS SageMaker
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Toronto, ON
- Full-time
We are looking for a highly experienced Senior AWS SageMaker / MLOps Engineer with 8+ years of overall IT experience and strong expertise in building, deploying, and operationalizing…

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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