ZipRecruiter

Log In

1

Full Stack Developer Intern Jobs in London, ON (NOW HIRING)

CARFAX

Senior Software Engineer - Dev Ops

London, ON · On-site

AI Developer Platform - Own and contribute to the architecture and operations of interactive ... Observability & Reliability - Contribute to the full observability stack implementation - designing ...

ALS

Mining Process Engineer

London, ON · Hybrid

CA$115K - CA$135K/yr

Working across the full control stack, from field instrumentation and PLCs to SCADA, advanced process control (APC), and data historian systems. This role combines hands-on programming with real ...

Proton

Senior Foundation Engineer (Drive)

London, ON · On-site

... Stack and Tools: * Languages we see daily is C#, TypeScript and Rust. We also need to provide ... Then we will do second generation in Rust with lessons learned and include full support of all ...

Helsing

Radio Frequency Engineer

London, ON · On-site

You'll work across the full chain, from antenna and front-end design through to link budgets and EW ... stack * Support field testing of RF and communications systems, including range trials and EW ...

Carmeuse

Environmental Area Manager

Ingersoll, ON

CA$120K - CA$159K/yr

Comprehensive benefits package that includes Health, Dental, Vision, and a full pension plan ... Work with operations and engineering to understand process emissions and develop data. * Interact ...

previous page

Showing results 21-32

All JobsFull Stack Developer Intern JobsFull Stack Developer Intern Jobs in London, ON

Full Stack Developer Intern information

What is a full stack developer intern?

A Full Stack Developer Intern is a trainee who assists in building both the front-end (user interface) and back-end (server, database) components of web applications. Interns in this role work under the guidance of experienced developers to learn and contribute to the entire software development process. They often use programming languages like JavaScript, Python, or Java, and frameworks such as React, Node.js, or Django. The internship provides practical experience in coding, debugging, and deploying web applications, preparing interns for a full-time developer position.

What are the key skills and qualifications needed to thrive as a full stack developer intern?

To thrive as a Full Stack Developer Intern, you need a strong grasp of front-end and back-end programming languages, such as JavaScript, HTML/CSS, and either Node.js, Python, or Java, along with a relevant academic background in computer science or a related field. Familiarity with version control systems like Git, web frameworks (e.g., React, Express), and databases (SQL/NoSQL) is typically required. Strong problem-solving abilities, eagerness to learn, and effective communication skills help interns collaborate with teams and adapt to new technologies. These competencies are crucial for contributing to real-world projects, quickly adapting to workplace demands, and laying the foundation for a successful development career.

What types of projects and technologies can a full stack developer intern expect to work on during their internship?

As a Full Stack Developer Intern, you'll typically be involved in projects that span both front-end and back-end development, such as building web applications, developing new features, or troubleshooting existing systems. You may work with technologies like JavaScript frameworks (e.g., React or Angular) for the front end, and languages such as Python, Java, or Node.js for the back end. It's common to collaborate closely with other developers, designers, and sometimes product managers, gaining exposure to the full software development lifecycle. Interns often participate in code reviews, agile sprints, and team meetings, providing valuable hands-on experience and learning opportunities.

How to get an internship for a full stack developer?

To secure a full stack developer internship, candidates should build a strong portfolio demonstrating skills in front-end and back-end technologies, such as JavaScript, HTML, CSS, and frameworks like React or Node.js. Gaining experience through personal projects, contributing to open-source, and obtaining relevant certifications can improve chances, along with applying through company career portals or internship programs and preparing for technical interviews. Having a solid understanding of version control systems like Git and good problem-solving skills are also beneficial.

Is a full stack developer intern still in demand?

Full stack developer internships remain in demand as companies seek candidates with skills in front-end and back-end technologies, including JavaScript, Python, and frameworks like React or Node.js. Internships provide valuable experience and can lead to full-time roles, especially as demand for versatile developers continues to grow in tech industries.

What are the most commonly searched types of Full Stack Developer jobs in London, ON?

The most popular types of Full Stack Developer jobs in London, ON are:

What are popular job titles related to Full Stack Developer Intern jobs in London, ON?

For Full Stack Developer Intern jobs in London, ON, the most frequently searched job titles are:

What cities near London, ON are hiring for Full Stack Developer Intern jobs?

Cities near London, ON with the most Full Stack Developer Intern job openings:

Full Stack Developer Intern jobs near you
Infographic showing various Full Stack Developer Intern job openings in London, ON as of August 2026, with employment types broken down into 84% Full Time, 10% Part Time, 5% Contract, and 1% Nights. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Senior Software Engineer - Dev Ops

CARFAX

London, ON

Full-time

Medical, Retirement

Re-posted 8 days ago

Job description

Join Team CARFAX as a Senior Software Engineer - Dev Ops
 
We are looking for a seasoned Senior Software Engineer - Dev Ops to join our platform team and take an active role in designing, scaling, and operating the infrastructure that powers Large Language Model (LLM) development and hosting. This is a high-impact, highly technical position where you will own critical platform components, drive architectural decisions, and directly shape the reliability, performance, and security of our AI infrastructure.
 
At its core, this is a Kubernetes-first, cloud-native platform engineering role. We care deeply about your ability to architect and operate scalable, resilient infrastructure for LLM workloads — the specific cloud or tooling you've built that experience on is secondary. Our current platform runs on AWS with EKS, Flyte, ArgoCD, JupyterHub, and the LGTM observability stack, and you'll be working within that environment — but we are far more interested in the depth of your platform thinking than in a specific vendor background.
 
If you are an engineer who thrives at the intersection of AI/ML and cloud-native infrastructure, who gets excited about solving the unique scaling and operational challenges that LLM workloads demand, and who wants to work on technology that sits at the absolute cutting edge of the AI industry — this role was built for you.
 
At CARFAX, we believe in the power of teamwork and value in-person interactions so that we can collaborate and thrive together. This position will require 2 days in the London, ON office per week, subject to change with future business needs.
 
What You'll Own:
 
LLM Platform Architecture — Actively participate in the design and evolution of the core infrastructure platform supporting LLM training, fine-tuning, and inference workloads at scale, contributing architectural decisions that balance performance, cost, and reliability across the full platform lifecycle.
 
Kubernetes & Advanced Autoscaling — Own the design and implementation of sophisticated K8s autoscaling strategies (HPA, VPA, KEDA, Cluster Autoscaler) tailored to the highly variable and GPU-intensive demands of LLM workloads. Our current environment is EKS, though equivalent production Kubernetes experience on GKE, AKS, or on-prem is equally valued.
 
ML Workflow Orchestration — Participate in the engineering and optimization of ML pipeline infrastructure, contributing to best practices for pipeline design, resource allocation, and workflow reliability across LLM training and evaluation workloads. We currently use Flyte — experience with comparable platforms such as Kubeflow, Airflow, or Prefect translates well.
 
AI Developer Platform — Own and contribute to the architecture and operations of interactive compute environments used by AI researchers and LLM engineers to develop, experiment, and prototype. We run JupyterHub today, though experience with equivalent multi-user ML development platforms is directly applicable.
 
CI/CD & GitOps — Participate in the development and ongoing improvement of GitOps workflows and CI/CD pipelines, contributing to deployment best practices and enabling rapid, reliable delivery of platform changes. Our current implementation uses ArgoCD — strong experience with GitOps principles and comparable tooling is what matters.
 
Observability & Reliability — Contribute to the full observability stack implementation — designing dashboards, defining SLOs, building alerting frameworks, and ensuring deep visibility into LLM workload performance and platform health. We use the LGTM stack (Loki, Grafana, Tempo, Mimir) — experience with Prometheus, OpenTelemetry, ELK, Datadog, or equivalent platforms is welcomed.
 
Cloud Infrastructure — Participate in cloud infrastructure design across compute (including GPU instance families), storage, networking, and IAM, with a strong emphasis on cost optimization and operational excellence. Our primary cloud is AWS — candidates with strong GCP or Azure backgrounds who are prepared to work in AWS are encouraged to apply.
 
Security & Compliance — Engage actively in the vulnerability assessment and remediation program across all platform components, contributing to security standards and ensuring the LLM platform meets organizational and regulatory compliance requirements.
 
Collaborative Engineering — Participate in technical design reviews, contribute to roadmap discussions, and serve as a knowledgeable resource and collaborative partner across AIOps and MLOps disciplines
 
Required Experience & Skills:
 
7+ years of experience in DevOps, Platform Engineering, MLOps, or a closely related infrastructure discipline.
 
Deep Kubernetes expertise — production experience operating Kubernetes at scale on any major managed platform (EKS, GKE, AKS) or on-premises, with advanced knowledge of scheduling, autoscaling, networking, RBAC, and cluster operations.
 
Cloud infrastructure proficiency — extensive experience designing and operating production workloads on at least one major cloud provider (AWS, GCP, or Azure), covering compute, storage, networking, and identity and access management
 
MLOps / AI Infrastructure experience — demonstrated experience building and operating infrastructure that supports ML training, model serving, or LLM workloads, including GPU resource management and scheduling at scale
 
CI/CD & GitOps — strong hands-on experience with GitOps principles and modern CI/CD pipeline design, using any mainstream tooling (ArgoCD, Flux, GitHub Actions, Tekton, or equivalent)
 
Observability Engineering — production experience designing and operating observability platforms including metrics, logging, and distributed tracing, using any modern stack (Grafana/LGTM, Prometheus, Datadog, ELK, or equivalent)
 
Infrastructure as Code — strong proficiency with Terraform, Helm, or comparable IaC and configuration management tooling.
 
Programming & Scripting — solid coding ability in Python and/or Go, with experience writing automation, tooling, and infrastructure integrations.
 
Security Mindset — hands-on experience with vulnerability scanning, remediation workflows, and cloud security best practices including RBAC hardening and secrets management
 
Strongly Preferred:
Direct experience with Flyte or comparable ML workflow orchestration platforms (Kubeflow, Airflow, Prefect, Metaflow)
Experience operating JupyterHub or equivalent multi-user interactive compute platforms at scale
Familiarity with LLM-specific infrastructure — model serving frameworks (vLLM, Triton, TorchServe), GPU cluster management, large-scale distributed training setups
Hands-on experience with AWS (EKS, EC2 GPU families, S3, IAM, VPC) as our current primary cloud environment
Experience with FinOps practices — cloud cost attribution, rightsizing, and spot/preemptible instance strategies for ML workloads
Relevant certifications: CKA / CKS, AWS/GCP/Azure Solutions Architect or DevOps Engineer, or equivalent
Who You Are:
A systems thinker who understands how architectural decisions ripple across reliability, performance, cost, and security — regardless of which cloud or tooling stack those decisions are made within
Operationally minded — you build things to be observable, maintainable, and resilient from day one
Deeply curious about AI and LLMs — you understand why the infrastructure you build matters and stay current with how the AI landscape is evolving
Proactive and ownership-driven — you identify problems before they become incidents and drive solutions to completion
An effective collaborator and communicator who can translate complex infrastructure concepts for AI researchers, data scientists, and engineering leadership alike
Comfortable operating with autonomy in a fast-moving environment where priorities evolve alongside the AI landscape
 
Why This Role Stands Out:
LLM infrastructure is one of the most technically demanding and strategically important engineering domains in the industry today. As a senior member of our AIOps team you will:
Directly shape the platform that enables LLM development and productionization — your contributions will have immediate, measurable impact
Work on genuinely hard infrastructure problems — GPU scheduling, large-scale distributed workloads, high-throughput model serving, and multi-tenant ML environments
Be positioned at the epicenter of the AI infrastructure space, one of the fastest growing and highest-demand engineering disciplines in the industry
Have a clear voice in technical direction — your experience and opinions on platform design are genuinely valued and actively sought
Bring your full experience to the table — whether you've built on AWS, GCP, Azure, or hybrid environments, your platform engineering expertise is what drives impact here
 
What’s in it for you: 
  • Competitive Compensation: Attractive salary, comprehensive benefits, and generous time-off policies. 
  • Flexible Work Schedules: Enjoy 4-day summer work weeks and a winter holiday break. 
  • Retirement Support: 401(k) / DCPP matching. 
  • Performance Rewards: Annual bonus program to recognize your contributions. 
  • Innovative Workspace: Casual, dog-friendly offices designed for creativity and collaboration. 
 
Hear from our Team: Our accolades speak for themselves:
  • 13X Virginia Business Best Places to Work
  • 12X Washingtonian Great Places to Work
  • 9X Washington Post Top Workplace
  • 5X USA Today Top Workplace
  • 5X St. Louis Post-Dispatch Best Places to Work
Vacancy Status:
This posting is for an existing vacancy.
 
Base Salary:
The anticipated base salary range for this position is CAD $92,500 to $136,000 annually. Final base salary will be determined based on geographical location, experience, and qualifications.
 
Benefits:
Join a company that values your total wellbeing. Carfax offers competitive compensation, comprehensive healthcare coverage, and the chance to make a meaningful impact in an industry-leading organization.  Our benefit offerings can be found at: CARFAX Careers.
 

Apply