Jobs in Canada

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Added 1 day ago
O
Spécialiste principal(e) en architecture de données et intelligence artificielle
Onepoint
Montreal, QC
- Full-time
Définir les architectures d’apprentissage automatique ainsi que les pratiques MLOps et LLMOps couvrant le déploiement, l’évaluation, l’observabilité et la gestion des versions;
Added 1 day ago
Développeur.se - opérations liées à l’apprentissage automatique / MLOps Developer
Electronic Arts
Vancouver, BC
As an MLOps Engineer, you will work closely with researchers to optimize models, help shape the data they need for training, and instrument the system to measure and improve model…
Added 1 day ago
M
Intermediate DevOps Engineer
MDA
Richmond, BC
- Full-time
We are looking for a DevOps Specialist with experience with MLOps to bridge the gap between machine learning development and production engineering. In this role, you will design, build,…
Added 1 day ago
NT
Intermediate Machine Learning Developer
Novarc Technologies Inc.
Vancouver, BC · Greater Vancouver Metropolitan Area
- Full-time
…for an experienced and hands-on Intermediate Machine Learning Developer to join our growing team and support existing products and help us develop new…
Added 1 day ago
TT
AI Engineer
Trojan Technologies
London, ON
- $90,000 to $120,000 CAD / year
- Full-time
Experience with MLOps, including model versioning, monitoring, and retraining pipelines.
Added 1 day ago
AC
Data Engineering Team Lead
Atlas Corp.
Vancouver, BC
- $120,000 to $130,000 CAD / year
Experience with machine learning platforms, MLOps, streaming technologies, or real-time analytics.
Added 1 day ago
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Senior AI Application Developer-Evergreen
Fujitsu
Montreal, QC
- Full-time
Manage the deployment, monitoring, and maintenance of AI solutions in production environments using LLMOps/MLOps practices, CI/CD pipelines, and version control.
Added 1 day ago
EC
Senior AI Engineer
E+E Consulting
Montreal, QC
- Full-time
Montreal, QC | Hybrid, 2–3 days per week onsite | Ayata.AI
Added 1 day ago
IF
Senior Data Analyst,
iA Financial Group
Toronto, ON · Montreal, QC · Quebec, QC
- Full-time
Implement development and production best practices, including CI/CD, DevOps, and MLOps, to ensure solution traceability, monitoring, reproducibility, quality, and long-term sustainability.
Added 1 day ago
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Principal AI/ML Engineer
lululemon
Vancouver, BC
- Full-time
…deep expertise in machine learning systems, generative AI, MLOps , and platform architecture to shape company-wide technical strategy and design of the enterprise AI platform and services,…
Added 1 day ago
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Senior Specialist, Agentic AI Engineering
McKesson
Mississauga, ON
- Full-time
Experience with AgentOps, LLMOps, MLOps, telemetry pipelines, monitoring dashboards, and AI cost optimization practices.
Added 1 day ago
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Principal Engineer - Open Source Data Platform (ODP)
Acceldata
Kitchener, ON
- Full-time
Experience with ML infrastructure, feature stores, or MLOps platforms.
Added 1 day ago
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AI/ML Lead (Sagemaker)
Iris Software Inc.
Toronto, ON
- Contract
Added 2 days ago
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Graph Data Scientist
Swoon
Toronto, ON
- Contract
Work arrangement: Hybrid, 3 days per week onsite
Added 2 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 2 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 2 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 2 days ago
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Principal, AI Agent Control & Governance
ATB
Edmonton, AB · Calgary, AB
- Full-time
…governance requirements directly into technical workflows, MLOps pipelines, and agent execution environments. This ensures innovation velocity is maximized while maintaining audit-ready…
Added 3 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 3 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 3 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 3 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 4 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 4 days ago
M
AI Scientist Intern - (Internship, Masters or Phd)
Mistral
Montreal, QC
- Internship
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes…
Added 4 days ago
LD
Engineering Manager, Agentic AI & Machine Learning
Loblaw Digital
Toronto, ON
- Full-time
Build for production at scale: Promote sound engineering practices across CI/CD, MLOps, LLMOps, security, responsible AI, incident management, and operational readiness.

MDA

Intermediate DevOps Engineer

Richmond, BC, V6V 2J3, Canada

The compensation range for this position is $78,000 - $108,000 annually. · Full-time

Apply on recruiting.ultipro.ca About employer

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Job details

Pay: The compensation range for this position is $78,000 - $108,000 annually.
Job type: Full-time
Experience: 3+ years of software development experience with at least 2 years focused on MLOps
Posting language: English
Posted: Nov 9, 2026

Original job description

ABOUT MDA SPACE

Building the space between proven and possible, MDA Space is a trusted mission partner to the global space industry. A robotics, satellite systems and geointelligence pioneer with a 55-year+ story of world firsts and more than 450 missions, MDA Space is a global leader in communications satellites, Earth and space observation, and space exploration and infrastructure. The global MDA Space team of more than 4,000+ space experts has the knowledge and know-how to turn an audacious customer vision into an achievable mission – bringing to bear a one-of-a-kind mix of experience, engineering excellence and wide-eyed wonder that’s been in our DNA since day one. For those who dream big and push boundaries on the ground and in the stars to change the world for the better, we’ll take you there. For more information, visit www.mda.space.

The Position

We are looking for a DevOps Specialist with experience with MLOps to bridge the gap between machine learning development and production engineering. In this role, you will design, build, and maintain the infrastructure and tooling that enables our AI and ML Analysts and Engineers to rapidly develop, deploy, monitor, and iterate on machine learning models at scale.

The DevOps Specialist is a core member of the Geointelligence DevSecOps and MLOps team. You will work at the intersection of Software Engineering, DevOps, and Machine Learning – ensuring our AI and ML systems are reliable, reproducible, and efficient. This is a high-impact role that will shape how we deliver AI – powered products to our customers.

Responsibilities:

Platform

Design and evolve a scalable, secure MLOps platform that include model registry, CI / CD / CT, feature store, experiment tracking, and monitoring built on Kubernetes, Terraform for both on premise and cloud (AWS)
Develop reusable infrastructure-as-code modules for data ingestion, model serving, and auto scaling.

Model Lifecycle Management

Implement automated CI / CD pipelines that take model code, data schemas, and container images from development to production with minimal down time
Integrate model versioning with data lineage and meta data tracking

Operational Excellence

Build observability platform for latency, throughput, drift detection, and resource utilization of live models
Develop automated alerts and self healing mechanisms for model anomalies or hardware failures

Collaboration and Enablement

Partner with AI / ML Analysts to translate research notebooks into production ready pipelines, providing tooling, best practice guidance, and code reviews
Collaborate with Corporate IT, Technical Governance, and Platform Products to up-skill teams on MLOps best practices and platform usage.

Security and Compliance

Implement data encryption in transit and at rest, role-based access control, and secure secret management meeting both government and industry standards.
Participate in risk assessments and support audit activities for Geointelligence AI and ML systems.

Continuous Improvement

Evaluate emerging technologies and recommend adoption where they add measurable value
Contribute to open source components and publish internal libraries to foster a reusable ecosystem

Qualifications/ Requirements:

Sc in Computer Science, B.Eng Engineering, Data Science, or related field
3+ years of software development experience with at least 2 years focused on MLOps
Proficiency in Python and at least one compiled language such as C / C++, Go, Rust
Proficiency with Docker containers and Kubernetes
Infrastructure as code (Terraform, Ansible)
CI / CD / CT tooling
Model serving frameworks
Experiment / metadata tracking
Monitoring and Observability
Cloud Platform
Experience with AWS services for compute including EKS, storage, and AI / ML e.g. SageMaker / Bedrock
Excellent communication – the ability to translate technical concepts for non-technical stakeholders
Proactive problem solver, comfortable working in a fast paced, mission critical environment

Comments/Special Considerations:

Successful candidates must obtain and hold security clearance at the reliability status level, and pass security assessment for the Controlled Goods Program (CGP).

We’re a dream team of purpose-driven, collaborative and passionate people, and we are constantly looking for others to join #TeamMDA to ignite new and innovative approaches to problem-solving that push us forward to improve life on and above Earth. If you’re excited to expand our place in space and driven to inspire the next generation, we’ll take you there.

We have entered a new era of exploration and development, and MDA welcomes all who yearn to suit up and be part of it. An equal opportunity employer prizing diversity, integrity and collaboration, we are committed to growing MDA’s and Canada’s leadership in this next golden age.

MDA provides competitive compensation and benefits packages for its employees at all locations. As a team member of MDA, you and your qualified dependents are eligible to participate in a benefit plan that ensures a comprehensive level of protection through competitive health care including; extended healthcare and flexible drug plans, dental and vision benefits, disability income protection, life insurance, group retirement savings plans; and an employee and family assistance program.

MDA is proud to provide accommodation(s) during the recruitment process. Should you require any accommodations, please indicate this on your application/cover letter and we will work with you to meet your accessibility needs.

The compensation range for this position is $78,000 - $108,000 annually. The specific compensation offered will be based on the qualifications and experience of the successful candidate.

#Sp #IND

Apply on recruiting.ultipro.ca About employer

More about this job

Responsibilities

Design and maintain a scalable MLOps platform to enable the development, deployment, and monitoring of machine learning models. Collaborate with AI/ML analysts to translate research into production-ready pipelines while ensuring system reliability and security.

Requirements

Requires a degree in Computer Science, Engineering, or Data Science with at least 3 years of software development experience, including 2 years in MLOps. Proficiency in Python, containerization, and infrastructure-as-code tools is essential.

Skills

DevOps
MLOps
Python
Kubernetes
Terraform
AWS
CI/CD
Docker
Infrastructure as code
Model lifecycle management
Observability
Data lineage
Ansible
C++
Go
Rust

Benefits

Extended healthcare
Flexible drug plans
Dental benefits
Vision benefits
Disability income protection
Life insurance
Employee and family assistance program

Visa sponsorship

Not detected in the job text

Keywords

DevOps
MLOps
Python
Kubernetes
Terraform
AWS
CI/CD
Docker
Infrastructure as code
Model registry
Feature store
Observability
Ansible
C++
Go
Rust
EKS
SageMaker
Bedrock
Geointelligence
DevSecOps
Data lineage
Metadata tracking
Drift detection
Role-based access control
Security clearance
Controlled Goods Program
Software engineering
Machine learning
Cloud computing

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Work requirements

Jobs in Canada