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Added 1 month ago
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Senior DevOps Engineer
Aptiv
Ottawa, ON
- Full-time
We are looking for a Senior DevOps Engineer who can help strengthen the reliability, automation, build, release, and developer experience of our cloud platform products. This role is not…
Added 4 months ago
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Senior Software Development Engineer
Wagepoint
Remote, Canada
- $130,000 to $160,000 CAD / year
- Full-time
- Remote
We're looking for a talented Senior Software Development Engineer who enjoys tackling hard problems and wants to create meaningful impact for small businesses across Canada. You'll play a…
Added 4 months ago
Verification and Validation Engineer - Test & Automation
Octasic
Montreal, Quebec
We are looking for a hands-on and automation-oriented engineer to support system verification and validation activities across complex wireless and embedded platforms.
Added 4 months ago
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Apps Development Sr Manager - Vice President
Citi
Mississauga, Ontario
- Full-time
The Senior DevOps Engineer must be an experienced hands-on engineer passionate about solving complex infrastructure and automation challenges.
Added 4 months ago
EI
Senior Integrations Developer / AI Data Integration Engineer
Engineered Intelligence Inc.
Mississauga, Ontario
- Full-time
We are looking for an experienced and hands-on Senior Integrations Developer / AI Data Integration Engineer to help lead the evolution of our modern data integration platform. This role…
Added 2 months ago
GM
Senior Software Developer - Test Automation
General Motors
Remote, Canada
- Full-time
- Remote
You will join our engineering organization as a Software Development Engineer in Test (SDET), responsible for building robust, scalable, and automated testing solutions that ensure the…
Added 4 months ago
GE
Senior Software Engineer
GFL Environmental Inc.
Vaughan, Ontario
- Full-time
We are seeking a highly skilled Senior Full-Stack Developer with 6+ years of experience to lead the digital transformation of our core enterprise applications. You will be responsible for…
Added 4 months ago
Développeuse ou développeur en développement et exploitation (DevOps) sénior, Asset Manager / Senior DevOps Developer, Asset Manager
Unity Technologies
Montreal, Quebec
Comme développeuse ou développeur en développement et exploitation (DevOps) sénior, vous serez responsable de la manière dont l’Asset Manager est déployé dans notre offre infonuagique…
Added 5 months ago
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[ Fastwater Staffing ] Senior Mission and Operations Satellite Systems Engineer | Relocate to Montreal, Canada ( Full Relocation Package )
HIKINEX
Montreal, Quebec
- Full-time
As part of the System Engineering Department, the Senior Mission and Operations Satellite System Engineer will participate, and coordinate the work needed for the analysis, planning and…
Added 1 month ago
RR
Principal Android Engineer
Rakuten Rewards
Toronto, ON · CN-Yonge Sheppard Center
- Full-time
We are seeking a visionary Principal Android Engineer to lead the evolution of our client application architecture and platform capabilities. You’ll define and drive the technical direction…
Added 2 months ago
Senior Software Engineer
NexHealth
Toronto, ON
5+ years of experience as a software engineer, with a focus on building scalable back-end systems and platforms.
Added 4 months ago
Principal Platform Engineer - Kubernetes & Cloud Infrastructure
Ombud
Quinte West, Ontario
We're hiring a Principal Platform Engineer to own that foundation. This is a senior individual contributor role with broad architectural authority. You will not have direct reports. You…
Added 4 months ago
C++ Developer
Glint Tech Solutions LLC
Toronto, Ontario
We are partnering with one of Canada's leading institutional investors to find a Senior C++ Engineer who will directly impact global trade activities and deliver long-term value to 20M+…
Added 4 months ago
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Senior Manager, AWS Technical Support
Ingram Micro
Remote, Canada
- $150,000 to $165,000 CAD / year
- Full-time
- Remote
Role: The Senior Manager of AWS Technical Support leads a team of high-performing technical support professionals delivering world-class support to mid-tier and enterprise customers…
Added 5 months ago
IN
Senior Data Engineer
IKO North America
Mississauga, Ontario
- Full-time
…flows? If so, we have the perfect opportunity for you! As a Senior Data Engineer, you will ensure scalable and efficient data systems by addressing global operational demands, maintaining…
Added 2 months ago
Senior Software Engineer
AutoTrader.ca
Toronto, ON
We’re looking for a Senior Software Engineer who takes end-to-end ownership, thrives in ambiguity, and wants to build systems that matter. This role is central to modernizing our platform…
Added 2 months ago
Senior Software Engineer, CMS (Auto Repossession & Remarketing)
AutoTrader.ca
Toronto, ON
We’re looking for a Senior Software Engineer who takes end-to-end ownership, thrives in ambiguity, and wants to build systems that matter. This role is central to rethinking and rebuilding…
Added 5 months ago
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Senior Site Reliability Engineer
SimCorp
Toronto, Ontario
- Full-time
As a Senior Site Reliability Engineer, you will be embedded within one of our Product Areas, taking ownership of specific responsibility domains where your experience, interests, and growth…
Added 5 months ago
Tech Lead
LauraMac, LLC
Quinte West, Ontario
…Tech Lead, you’ll play a dual role - acting as both a hands-on engineer and a technical leader for a Scrum team composed of 5 engineers and 2…
Added 5 months ago
SI
IT Senior Analyst, Enterprise Applications – Power BI Developer - Analytics
Saputo Inc.
Remote, Canada
- Full-time
- Remote
The Power BI Developer is a business‑focused analytics role responsible for partnering closely with business teams to design, deliver and sustain insightful Power BI dashboards and reports.…
Added 5 months ago
SI
IT Architect, Architecture & Analytics – Enterprise Analytics
Saputo Inc.
Remote, Canada
- Full-time
- Remote
…Silver, Gold architecture), working closely with Governance and DevOps Specialist, and Data Engineer…
Added 5 months ago
MS
Senior Software Engineer - AI/Computer Vision (Camera Systems)
Motorola Solutions
Vancouver, British Columbia · Toronto, Ontario
- Full-time
As a Senior Software Engineer in our camera systems group, you will play a crucial role in designing, developing, and optimizing C++ code for embedded systems. You will work on implementing…
Added 5 months ago
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Intermediate Software Engineer
AltaML
Calgary, AB · Edmonton, AB · Toronto, ON
- Full-time
The Intermediate Software Engineer independently owns and delivers well-defined, small-to-medium complexity user stories end to end. You work AI-first by default - using Claude Code and…
Added 5 months ago
GE
Senior Integration Engineer (Future oppourtunity)
GFL Environmental Inc.
Vaughan, Ontario
- Other
We are seeking a Senior Integration Engineer to design, develop, and maintain robust data integration solutions. You will focus heavily on real-time data streaming via Apache Kafka and…
Added 1 month ago
DevOps Engineer
Later
Vancouver, BC
We’re looking for a DevOps Engineer to help support and grow Later’s cloud infrastructure, DevOps practices, and emerging MLOps capabilities.

Later

DevOps Engineer

Vancouver, BC, Canada

$ 120,000 - 140,000 CAD

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Job details

Pay: $ 120,000 - 140,000 CAD
Posting language: English
Posted: Sep 3, 2026

Original job description

Later is the world’s most intelligent influencer marketing company, built to give brands the confidence to create unforgettable campaigns. By combining real creator relationships, trusted intelligence, and expert guidance, Later removes fear and guesswork from one of marketing’s most visible investments.

Built on a native, AI-powered platform and more than a decade of proprietary data - including billions of social interactions, impressions, and $2.4B+ in verified influencer-driven purchases - Later helps teams understand what will work before they launch.

By combining trusted insight with expert guidance, Later removes guesswork from influencer marketing, enabling brands to choose the right creators, execute fully managed campaigns, and drive meaningful growth across awareness, engagement, and revenue. Trusted by leading enterprise brands including Nike, Wayfair, Unilever, and Southwest Airlines, Later bridges creativity and performance so campaigns don’t just look good - they deliver results. Learn more at later.com.

About this position:

We’re looking for a DevOps Engineer to help support and grow Later’s cloud infrastructure, DevOps practices, and emerging MLOps capabilities.

This role reports to the Infrastructure team and is primarily focused on DevOps, AWS, Kubernetes, CI/CD, Terraform, while also helping support the infrastructure needs of our Data teams. You’ll work closely with senior engineers, platform teams, data scientists, and product engineers to help build the systems that support application delivery, data workflows, model experimentation, and ML deployment.

This is a great role for someone who has a solid DevOps foundation and wants to grow deeper into cloud infrastructure, Kubernetes, GitOps, and MLOps. You’ll help maintain reliable infrastructure, improve deployment workflows, automate repeatable tasks, and support the systems that allow engineering and data teams to move faster and more safely.

What you'll be doing:

Strategy

Support the development and execution of the infrastructure roadmap across DevOps, and MLOps, aligned with product, and data/AI growth plans.
Partner with engineering, data, and ML teams to ensure scalability, reliability, security, and automation are built into both application infrastructure and machine learning workflows.
Help evaluate and adopt DevOps and MLOps tools that improve system efficiency, observability, developer experience, model deployment, and operational reliability.
Contribute to platform standards that make infrastructure, CI/CD, data pipelines, and ML systems more repeatable, secure, and easier to operate.
Support the evolution of cloud-native practices that enable faster product delivery while also preparing the platform for future AI and ML initiatives.

Technical/ Execution

Build and manage infrastructure to deploy ML models into production reliably using CI/CD pipelines , Flask-based APIs, and orchestration tools (e.g., Airflow, Kubeflow, or Argo Workflows).
Automate training pipelines, model registry, validation, deployment, and rollback strategies using tools such as Amazon SageMaker Interface and Postman for testing.
Build systems to monitor model performance, latency, data drift, and resource usage using Amazon CloudWatch, Prometheus, and Grafana.
Design and maintain tools and systems to support model versioning, experiment tracking (e.g., MLflow, Amazon SageMaker Studio Notebooks), and reproducible training workflows.
Operate across GCP and AWS to manage training/inference infrastructure, BigQuery datasets, and GPU workloads.
Use tools like Terraform or CloudFormation to manage cloud infrastructure in a scalable, repeatable manner.
Work with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support their end-to-end ML workflows.

Team / Collaboration

Partner with Product and Data teams to streamline CI/CD workflows, GitOps practices, and deployment processes that support both application delivery and data/ML workflows.
Work closely with Data teams to support reliable infrastructure for data pipelines, model experimentation, training workflows, and production ML deployments.
Collaborate with Product teams to understand platform needs and ensure infrastructure decisions support product reliability, scalability, and delivery speed.
Share documentation, runbooks, and best practices that help Product and Data teams deploy, monitor, and troubleshoot systems with more autonomy.
Support a collaborative DevOps and MLOps culture by helping teams adopt automation, observability, and repeatable deployment patterns.

Research/Best Practices

Stay current with cloud-native, DevOps, data infrastructure, and MLOps trends, identifying tools, patterns, and practices that can improve reliability, automation, scalability, and delivery speed.
Continuously evaluate infrastructure, CI/CD pipelines, data workflows, model deployment processes, performance, cost, and efficiency, recommending improvements that align with product, engineering, and data team goals.
Contribute to documentation, runbooks, incident reviews, and post-mortem processes to strengthen operational learning across both DevOps and MLOps practices.
Help define and share best practices for infrastructure-as-code, GitOps, observability, secure deployments, data pipeline reliability, and ML workflow automation.
Look for opportunities to simplify systems, reduce manual work, and improve the developer and data team experience through better tooling, automation, and platform standards.

What success looks like:

First 30 Days - Learn, Support, and Understand

In the first 30 days, the candidate will focus on learning Later’s cloud infrastructure, Kubernetes environments, AWS services, CI/CD workflows, and data/ML platform components.
They will begin supporting existing deployment pipelines, observability tools, infrastructure documentation, and operational workflows. They will also start becoming familiar with GPU-enabled workloads, SageMaker environments, notebooks, model training jobs, and current ML deployment processes.
By the end of 30 days, the candidate should understand how our DevOps and MLOps systems are structured, where support is needed, and how Product and Data teams use the platform.
You are recognized internally as a trusted partner who supports operational excellence, improves platform reliability, and helps raise technical standards across DevOps and MLOps practices.

First 60 Days - Contribute, Automate, and Improve

By 60 days, the candidate will begin taking ownership of smaller infrastructure and automation tasks across Kubernetes, AWS, CI/CD, and ML platform workflows.
They will help improve deployment pipelines for applications, infrastructure, and ML workflows, making them more consistent, automated, and easier for teams to use. They will also support GPU node provisioning, monitoring, and optimization for training, experimentation, and inference workloads.
The candidate will contribute to SageMaker support, including notebooks, model training jobs, access controls, monitoring, and repeatable deployment patterns. They will also help improve documentation, runbooks, alerting, and troubleshooting processes.

First 90 Days - Own, Optimize, and Scale

By 90 days, the candidate should be contributing with more independence across DevOps and MLOps workflows.
They will help improve reliability, scalability, security, and observability across Kubernetes clusters, AWS infrastructure, GPU-enabled workloads, SageMaker environments, and data/ML platform components.
They will support production-ready ML workflows by helping improve experimentation, model deployment, monitoring, rollback, troubleshooting, and operational readiness. They will also help ensure security and compliance requirements are integrated into infrastructure, CI/CD, data pipelines, SageMaker workflows, and platform operations.
By the end of 90 days, the candidate should be recognized as a trusted partner to Product and Data teams, helping reduce operational overhead through automation, documentation, alerting, GPU resource management, and repeatable platform standards.

What you bring:

2–5 years of hands-on DevOps or cloud engineering experience in production environments.
Expertise with Kubernetes (EKS), Helm, and microservices.
1-2 years AWS and SageMaker Experience.
1-2 years creating data pipelines
1-2 years with LLM deployments on Kubernetes
1-2 years with kubernetes clusters using nodes that have GPU
Proven track record using Terraform for scalable, auditable Infrastructure as Code.
A collaborative, solution-oriented mindset and a passion for automation and continuous improvement.

How you work:

Driven by Impact: You deliver results that matter - prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast - challenging the status quo with a mindset of improvement.
Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive - removing roadblocks, sharing insights, and keeping morale high.
Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted.

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range:

$ 120,000 - 140,000 CAD

Where we work:

We have offices in Boston, MA; Vancouver, BC; and Vancouver, WA. For select positions, we are open to hiring fully remote candidates. We post our positions in the location(s) where we are open to having the successful candidate be located.

Diversity, inclusion, and accessibility:

At Later, we are committed to fostering a culture rooted in an inclusion-first mindset at every level of the company, embracing the importance of hiring and building teams for culture add rather than culture fit. We openly build and maintain unbiased hiring, pay, and promotion practices to create a foundation for an equitable workplace, paving the way for systemic change.

We are committed to creating a diverse environment and are proud to be an equal opportunity employer. All applications will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, national origin, disability, or age. Please let us know if you require any accommodations or support during the recruitment process.

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More about this job

Responsibilities

Support and grow cloud infrastructure, DevOps practices, and MLOps capabilities to enable application delivery and ML deployment. Collaborate with data and product teams to automate training pipelines, monitor model performance, and maintain scalable infrastructure.

Requirements

Requires 2-5 years of DevOps experience with expertise in Kubernetes, AWS, and Terraform. Specific experience with SageMaker, LLM deployments on Kubernetes, and GPU-enabled nodes is required.

Skills

Kubernetes
AWS
Terraform
CI/CD
MLOps
SageMaker
Helm
GitOps
Infrastructure as Code
GPU Workloads
Prometheus
Grafana
Airflow
Flask
GCP
BigQuery

Benefits

Benefits plans

Visa sponsorship

Not detected in the job text

Keywords

DevOps
MLOps
Kubernetes
AWS
EKS
Terraform
SageMaker
CI/CD
GitOps
Helm
GPU
LLM
Airflow
Kubeflow
Argo Workflows
Flask
CloudWatch
Prometheus
Grafana
MLflow
GCP
BigQuery
Infrastructure as Code
Microservices
Data Pipelines
Observability
Model Versioning
Cloud-Native
Postman
CloudFormation

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