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Added 12 mins ago
MC
SOLUTION ARCHITECT TECHNICAL ARCHITECT (35734)
Myticas Consulting
Toronto, ON
- Full-time
…Engineering, Technical Consultants, Software Engineers, QA, DevOps, Security, Cloud, and implementation…
Added 12 mins ago
CI
Senior R&D Java Developer
Calian in Space & Technology
Montreal, QC
- Contract
Extensive knowledge of Azure cloud development, deployment pipelines, and DevOps practices.
Added 12 mins ago
AI
Senior AWS Data Engineer - 10+yrs
Apptoza Inc.
Toronto, ON
- Contract
Familiarity with CI/CD pipelines and DevOps practices.
Added 12 mins ago
MC
Manager – Banking Cloud & Platform Engineering (35857)
Myticas Consulting
Toronto, ON
- Full-time
Work with technical teams utilizing Infrastructure-as-Code, CI/CD, containers, Kubernetes, APIs, DevOps, and modern application delivery practices.
Added 12 mins ago
CG
Senior R&D Java Developer
Calian Group
Montreal, QC
- Full-time
Extensive knowledge of Azure cloud development, deployment pipelines, and DevOps practices.
Added 12 mins ago
MC
Senior QA Engineer III – Automation | Banking | API | Kafka | ETL (35729)
Myticas Consulting
Ottawa, ON
- Full-time
Collaborate with Developers, Business Analysts, Product, DevOps, and QA teams throughout the software delivery lifecycle.
Added 12 mins ago
E
Platform or DevOps Engineer
entOS
Engineer, BC
- Full-time
5+ years in platform engineering, DevOps, or cloud infrastructure
Added 14 mins ago
CL
Senior Backend Developer- .NET
Charger Logistics Inc.
Brampton, ON
- Full-time
…mesh, and observability platforms. You will work closely with DevOps, QA, and frontend teams to ensure high availability, scalability, and maintainability of our…
Added 14 mins ago
PC
Deals Real Assets, Data Engineering & Digital Solutions, Senior Associate
PwC Canada
Vancouver, BC
- Full-time
Automate data workflows and implement CI/CD practices for data pipelines using Azure DevOps or GitHub Actions to ensure quality and rapid deployment
Added 14 mins ago
MC
DevOps Specialist - Kubernetes (35700)
Myticas Consulting
Ottawa, ON
- Full-time
Added 14 mins ago
QC
Quality Assurance Engineer
Quarry Consulting
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Experience with CI/CD pipelines, Git, Jenkins, GitLab CI, Azure DevOps, or similar delivery tooling.
Added 30 mins ago
N
Information Security Engineer (Cloud) - Contract
Numeris
Toronto, ON
- Full-time
Partner directly with internal DevOps, Infrastructure, and Systems teams to translate posture findings into clear remediation tasks, track remediation timelines, and verify fixes.
Added 43 mins ago
R&
Developer - Full Stack – Senior
Robertson & Company Ltd.
Toronto, ON
- Contract
Proficiency with CI/CD pipelines, DevOps practices, source control, automated testing, and infrastructure-as-code
Added 43 mins ago
TS
Azure Architect
TECONICA SOFTWARES
Toronto, ON
- Contract
Absolutely. Based on the request in the image, I’d reposition this as a Microsoft Azure Platform Engineer / DevOps Engineer role rather than a Terraform-heavy generic DevOps role.
Added 43 mins ago
R&
Software Developer - Full Stack – Senior
Robertson & Company Ltd.
Toronto, ON
- Contract
Proficiency with CI/CD pipelines, DevOps practices, source control, automated testing, and infrastructure-as-code
Added 43 mins ago
IG
Python Developer
Insight Global
Toronto, ON
- $40 to $45 CAD / hour
- Contract
…Familiarity with source control tools such as Git or Azure DevOps • Knowledge of Software Development Lifecycle (SDLC) practices • Experience supporting internal business applications or…
Added 43 mins ago
ET
Senior Product Manager, Integration & Data Platforms
Encore Technical Solutions Inc.
Toronto, ON · Greater Toronto Area, Canada
- Contract
Added 43 mins ago
C
Sr Product Manager
CGI
Halifax, NS
- Full-time
Strong understanding of Agile/Scrum methodologies and experience with tools such as Azure DevOps (ADO), Jira, and Confluence.
Added 43 mins ago
A
Senior AI Platform Engineer (MLOps)
Akkodis
Toronto, ON
- Contract
Experience with GitHub Actions, Jenkins, Azure DevOps, or similar CI/CD technologies
Added 43 mins ago
P
Dynamics 365 / Power Platform Developer
ProxyLink
Toronto, ON
- Contract
…Power Platform, Azure, .NET, C#, JavaScript, Dataverse, APIs, DevOps, and cloud-based application development. Experience with Dynamics 365 Customer Service and enterprise CRM…
Added 43 mins ago
P
Software Engineer
ProxyLink
Toronto, ON
- Contract
Added 43 mins ago
QT
Terraform Solution Architect
Q1 Technologies, Inc.
Toronto, ON · Greater Toronto Area, Canada
- $60 to $65 CAD / hour
- Contract
Experience: 5+ years of dedicated experience in Solutions Architecture or senior DevOps Engineering roles.
Added 43 mins ago
C
Développeur Java
CGI
Montreal, QC
- Full-time
Bonne compréhension des pratiques DevOps, CI/CD, conteneurisation et déploiement sur Kubernetes.
Added 45 mins ago
C
Sr. Manager, Production Application Support
CIBC
Toronto, ON
- Full-time
…with Autosys and Feedhub, Version Control Software, Agile and DevOps concepts, DataPower, Jenkins, Github. You have strong knowledge of: Microsoft Windows, Linux RedHat and Unix Solaris…
Added 45 mins ago
R
Spécialiste, Ingénierie Logicielle / Specialist, Software Engineering
RTX
Longueuil, QC
- Full-time
Mettre à profit l’expertise en matière de DevOps, GitHub et Azure DevOps (ADO) pour développer ou moderniser des outils logiciels d’analyse.

Akkodis

Senior AI Platform Engineer (MLOps)

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Nov 4, 2026
Experience: 5+ years of experience in MLOps, Machine Learning Engineering, AI Platform Engineering, Cloud Engineering, or related technical disciplines
Posting language: English
Posted: Oct 5, 2026

Original job description

Title: Senior AI Platform Engineer

Position Type: Contract

Duration: 12-Month Contract (Potential Extension)

Client Location: Toronto, Ontario

Work Model: Hybrid (Downtown Toronto - 3 days in office)

Engagement Model: Professional Services Engagement – B2B (Incorporated Consultants Preferred)

About the Engagement

Akkodis is partnering with a leading institutional investment and pension organization to engage an experienced Senior AI Platform Engineer (MLOps) to support the ongoing growth and operationalization of enterprise AI capabilities.

This is a highly technical, hands-on engineering role focused on building, deploying, governing, and operating machine learning and AI platforms at enterprise scale. The successful candidate will work closely with AI Governance, Cybersecurity, Enterprise Architecture, Platform Engineering, and AI Centre of Excellence teams to implement responsible AI controls, operationalize machine learning models, and establish scalable AI deployment standards.

While the role supports AI governance and responsible AI initiatives, the primary focus is technical implementation. The client is seeking a strong engineering professional with deep MLOps, machine learning operationalization, cloud engineering, and Python development experience who can translate governance requirements into automated controls, deployment processes, and platform capabilities.

This opportunity is ideal for someone who enjoys solving complex technical problems, building enterprise-grade AI capabilities, and working across infrastructure, machine learning, security, and platform engineering domains.

Services to be Provided:

Design, build, and maintain enterprise MLOps and LLMOps capabilities supporting AI and machine learning solutions
Develop and automate model deployment, monitoring, evaluation, governance, and lifecycle management processes
Build CI/CD pipelines and Infrastructure as Code solutions supporting AI and machine learning environments
Implement model governance, auditability, approval workflows, and operational controls within production AI platforms
Support implementation of responsible AI and AI governance requirements through technical controls and automation
Develop and maintain model tracking, lineage, experiment management, and reproducibility capabilities
Implement and enhance MLflow, Databricks, evaluation frameworks, and related platform services
Collaborate with Cybersecurity, Enterprise Architecture, and AI Governance teams to operationalize enterprise requirements
Build and support AI deployment patterns for machine learning, RAG, and generative AI solutions
Troubleshoot, debug, and resolve platform, deployment, performance, and operational issues
Create technical documentation, implementation standards, operational procedures, and support guides
Support platform reliability, observability, monitoring, incident management, and recovery processes
Implement cloud cost monitoring, optimization, and consumption management practices
Provide technical guidance and enablement to teams adopting enterprise AI capabilities
Communicate technical solutions and implementation outcomes to both technical and senior business stakeholders

Expertise Required

5+ years of experience in MLOps, Machine Learning Engineering, AI Platform Engineering, Cloud Engineering, or related technical disciplines
Strong hands-on Python development experience
Proven experience operationalizing machine learning models in enterprise production environments
Experience designing and supporting model lifecycle management, deployment, monitoring, and governance processes
Strong understanding of MLOps best practices, CI/CD, automation, testing, and software engineering principles
Experience with Databricks, MLflow, or comparable machine learning platform technologies
Experience working with cloud platforms such as Azure, AWS, or Google Cloud
Experience with Infrastructure as Code methodologies and tooling
Hands-on experience with Terraform and modern deployment automation practices
Experience with GitHub Actions, Jenkins, Azure DevOps, or similar CI/CD technologies
Experience troubleshooting complex distributed systems and production environments
Strong understanding of machine learning model operationalization, evaluation, and observability
Experience implementing secure deployment and access control patterns within cloud or AI environments
Excellent communication skills with the ability to engage both technical and non-technical stakeholders
Proven ability to operate independently and deliver within fast-paced and evolving environments

How to Apply

If you are interested in learning more, don't hesitate to apply today or check out Akkodis Canada website for more opportunities.

Important

This is a business-to-business engagement. Candidates must represent an incorporated entity, hold a valid business number, maintain appropriate insurance, and invoice for services rendered.

We thank all applicants for their interest in this opportunity. Only candidates meeting the above qualifications will be contacted for further discussions.

Accessibility:

At Akkodis, part of The Adecco Group, our purpose is simple: to make the future work for everyone. We live our values, Passion, Collaboration, Inclusion, Courage, and Customers at Heart, by fostering a workplace where diversity is celebrated and every voice matters. We encourage applications from individuals of all backgrounds and identities. Together, we’re making the future work for everyone.

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More about this job

Responsibilities

Design, build, and operate enterprise MLOps and LLMOps capabilities, including automated deployment, monitoring, evaluation, governance, and lifecycle management for machine learning and generative AI solutions. Implement secure, reliable, and cost-aware platform processes and controls, and collaborate with governance, cybersecurity, architecture, and engineering teams to establish standards and support adoption.

Requirements

Requires at least five years of relevant MLOps, machine learning engineering, AI platform, or cloud engineering experience, strong Python skills, and experience operationalizing models in enterprise production environments. Candidates should have hands-on experience with platforms such as Databricks or MLflow, cloud services, Terraform and Infrastructure as Code, CI/CD, model lifecycle processes, and production troubleshooting.

Skills

Python
MLOps
LLMOps
Machine Learning
Databricks
MLflow
Cloud Engineering
Terraform
Infrastructure As Code
CI/CD
Model Deployment
Model Monitoring
Model Governance
Generative AI
Retrieval-Augmented Generation
Observability

Visa sponsorship

Not detected in the job text

Keywords

MLOps
LLMOps
Python
Machine Learning
AI Platform Engineering
Databricks
MLflow
Azure
AWS
Google Cloud
Terraform
Infrastructure As Code
CI/CD
GitHub Actions
Jenkins
Azure DevOps
Model Deployment
Model Lifecycle Management
Model Monitoring
Model Evaluation
Model Governance
Experiment Management
Model Lineage
Responsible AI
Generative AI
Retrieval-Augmented Generation
Cloud Engineering
Observability
Access Control
Cost Optimization

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