Jobs in Canada

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Added 2 months ago
BO
Commercial Banking Relationship Manager
Bank of China (Canada)
Markham, ON
- Full-time
Originate new business opportunities across commercial lending, deposits, trade finance, and cross-border banking solutions · Work with internal teams across jurisdictions to support cross-border transactions and client needs
Added 2 months ago
FB
Manager, Commercial Real Estate
Fairstone Bank
Toronto, ON
- Full-time
Added 2 months ago
NC
Associate Veterinarian
NVA Canada
Kelowna, BC
- Part-time
Added 2 months ago
S
Industry - Central Kitchen - Hot Kitchens - Clerk Production
Sobeys
Delta, BC
- Full-time
Work night shifts and weekends as required · Must have previous food experience
Added 2 months ago
L
Team Lead
LensCrafters
Toronto, ON · Etobicoke, ON
- Full-time
Added 2 months ago
HA
Electrical Engineer (Mid-to-Senior Level)
Hazen and Sawyer
Calgary, AB
- Full-time
Prospective applicants must have 15+ years of experience in industrial electrical engineering and design · Candidate must have a good working knowledge of the Canadian Electrical Code (CEC) or National Electrical Code (NEC) and other related Codes
Added 2 months ago
DG
Detailer
Dilawri Group of Companies
Mississauga, ON
- Full-time
Added 2 months ago
CI
Account Executive
Compugen Inc
Ottawa, ON
- Full-time
Must have or be eligible for a Level II (SECRET) Canadian Government Security Clearance
Added 2 months ago
C
Golf Course Assistant Superintendent
Cabot
NS · Inverness, NS
- Full-time
Added 3 months ago
M
Technical Architect
Mphasis
Toronto, ON
- Full-time
Must have Structural thinking and goal-oriented approach to problem-solving
Added 2 months ago
VN
Account Manager, Influencer Marketing (4-Month Contract)
Viral Nation
Canada
- Contract
Added 2 months ago
C
Sr. Azure BSA ( Hybrid )
Cognizant
Toronto, ON
- Full-time
Added 2 months ago
ST
Vice President Hardware Engineering
SmartSkin Technologies
Fredericton, NB
- $150,000 to $200,000 CAD / year
- Full-time
Added 2 months ago
CN
Contract Administrator
Canadian Nuclear Laboratories
Chalk River, ON
- Contract
Working schedule: Five (5) days per week, seven and a half (7.5) hours per day for a thirty-seven and a half (37.5) hour work week
Added 2 months ago
CN
Training Specialist
Canadian Nuclear Laboratories
Chalk River, ON
- Full-time
Working schedule: Five (5) days per week, seven and a half (7.5) hours per day for a thirty-seven and a half (37.5) hour work week
Added 2 months ago
CN
Contract Administrator
Canadian Nuclear Laboratories
Chalk River, ON
- Contract
Working schedule: Five (5) days per week, seven and a half (7.5) hours per day for a thirty-seven and a half (37.5) hour work week
Added 2 months ago
PR
Registered Nurse (RN), Emergency
Peterborough Regional Health Centre
Peterborough, ON
- $41.15 to $58.98 CAD / hour
- Part-time
Added 2 months ago
H
Developer Fullstack - Java Angular
Highspring
Montreal, QC
- Full-time
Added 2 months ago
CE
Technical Recruiter
Canadian Executive Search Group (USA) Inc / Division of Arrow Group of Companies
London, ON
- Full-time
Added 2 months ago
U
Développeur(se) logiciel sénior, optimisation d'actifs 3D (C++) / Senior Software Developer, 3D Asset Optimization (C++)
Unity
Montreal, QC
- Full-time
Added 2 months ago
RU
Manager, Strategic Sourcing (18-month contract)
Recipe Unlimited Corporation
Vaughan, ON
- Contract
Added 2 months ago
FD
Accounts Receivables and Payable Manager
Frontier Dental CA
Markham, ON
- $80,000 to $100,000 CAD / year
- Full-time
Added 2 months ago
LM
Capture Manager Domestic Market
Lockheed Martin
Ottawa, ON
- $140,000 to $183,750 CAD / year
- Full-time
Added 2 months ago
T
Underwriter, Commercial Surety
Trisura
Toronto, ON
- Full-time
Added 5 months ago
B
administrative assistant
Bodycad
Quebec, QC
- Full-time

Mphasis

Technical Architect

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Jul 31, 2026

Original job description

POSITION / TITLE: MLOps Engineer (Cloud Engineer + DevOps)

Location: Canada

Job Overview

We are looking for an experienced MLOPs / LLMOPs Engineer with a strong background in deploying and monitoring machine learning and large language model (LLM) pipelines. The ideal candidate will have 10+ years of experience in MLOPs, with expertise in setting up end-to-end ML/LLM pipelines using open-source tools and cloud-native solutions on platforms like AWS, GCP, and Azure. This role requires hands-on knowledge in deploying, automating, and monitoring ML/LLM workflows, with a solid grounding in DevOps practices to ensure seamless CI/CD processes.

Responsibilities

Pipeline Design & Implementation:
- Design, build, and manage MLOPs and LLMOPs pipelines for data ingestion, model training, validation, deployment, and monitoring.
- Use open-source tools such as Mlflow, Kubeflow, DVC, and Airflow to automate and monitor machine learning workflows.
- Implement scalable LLM-specific solutions for model training and inference, optimizing resource allocation and deployment efficiency.
Cloud-native MLOPs Implementation:
- Set up and manage MLOPs pipelines in Primary in GCP (SageMaker, EKS, Lambda, S3), or have similar experience with GCP (Vertex AI, AI Platform Pipelines), and Azure (Machine Learning, AKS, Azure Functions).
- Manage model versioning, retraining, and deployment workflows on cloud platforms to ensure consistent performance and availability.
- Execute CI/CD pipelines for ML models with GitHub Actions, Jenkins, or GitLab CI.
Model Monitoring & Performance Optimization:
- Monitor models in production using Prometheus, Grafana, and Tensorboard, establishing observability metrics for model drift, accuracy, and latency.
- Collaborate with Data Engineering and ML teams to implement scalable and efficient pipelines
- Use A/B testing and shadow deployment strategies to validate and optimize LLM model performance in real-time.
LLM-specific Model Operations:
- Deploy and monitor LLMs for specific tasks, ensuring they adhere to performance SLAs and are optimized for cost.
- Understand techniques of fine-tuning, optimizing inference, and managing infrastructure costs for large LLMs.

Required Skills And Qualifications

Technical Skills – Good to have:

Proficiency with Kubernetes and Docker for container orchestration and model deployment.
Experience with open-source MLOPs tools (Mlflow, Kubeflow, DVC) and data versioning.
Hands-on experience with cloud-native ML tools in AWS, GCP, or Azure and associated ML services.
Knowledge of Python or Bash scripting for automating processes and custom integrations.

DevOps-Related Skills

Solid understanding of CI/CD practices and tools like GitHub Actions, Jenkins, or GitLab CI/CD to build and deploy ML/LLM models.
Proficient in infrastructure-as-code tools, such as Terraform or Ansible, to enable automated provisioning and configuration management.

Programming & Scripting

Python
SQL, No-SQL, PySpark (Optional)

AI/ML & Data Science - Good To Have

Supervised, Unsupervised Learning & Model evaluation metrics
NLP, RAG, GenAI, LLMs
Deep Learning (Sequential & Functional APIs) using Pytorch/TensorFlow
MLOPs & Mlflow Experiment Tracking
Explainable AI (XAI) LIME SHAP(Optional)

Cloud Platforms

(Primary: AWS) or Handons Expertise on any of cloud platforms
Azure AI/ML,
Google Vertex AI,
Databricks Studio

Education

Bachelors/ Master’s/PhD Degree in Mathematics, Statistics, Physics, Computer Science, Engineering, Data Science, or a related relevant degree from quantitative field.

Process Skills

Understanding of Agile and Scrum methodologies.
Ability to follow SDLC processes and contribute to technical documentation.

Behavioral Skills

Must have Structural thinking and goal-oriented approach to problem-solving
Self-motivated and capable of working independently with minimal management supervision.
Well-developed design, analytical & problem-solving skills
Excellent communication and interpersonal skills.
Excellent team player, able to work with virtual teams in several time zones.

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More about this job

Responsibilities

Design and manage end-to-end ML and LLM pipelines for data ingestion, training, and deployment using cloud-native solutions. Monitor production models for drift and performance while implementing CI/CD processes to ensure seamless delivery.

Requirements

Requires over 10 years of experience in MLOps with proficiency in cloud platforms and container orchestration. A degree in a quantitative field such as Computer Science or Mathematics is required.

Skills

MLOps
LLMOps
AWS
GCP
Azure
Kubernetes
Docker
Mlflow
Kubeflow
CI/CD
Terraform
Python
PyTorch
TensorFlow
GenAI
RAG

Visa sponsorship

Not detected in the job text

Keywords

MLOps
LLMOps
AWS
GCP
Azure
Vertex AI
SageMaker
Kubernetes
Docker
Mlflow
Kubeflow
DVC
Airflow
CI/CD
GitHub Actions
Jenkins
GitLab CI
Terraform
Ansible
Python
SQL
PySpark
PyTorch
TensorFlow
GenAI
RAG
NLP
Prometheus
Grafana
Agile

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Work requirements

Jobs in Canada