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Kernel Engineer Jobs in Ontario (NOW HIRING)

Ciena

Wavelogic Embedded Software Developer

Ottawa, ON · On-site

CA$127/hr

Apply Linux kernel, TCP/IP stack, forwarding tables, IP filters, VLANs, and memory management ... Collaborate with engineering, architecture, and verification teams to resolve issues and support ...

Tiger Analytics Inc.

Gen AI Engineer

Toronto, ON · On-site

We are looking for a highly skilled AI Engineer with 7+ years of experience in software engineering ... Kernel. * Ability to manage orchestration, tool integration, and robust error handling for non ...

Clockwork.io

CA$150K - CA$230K/yr

Kernel subsystems, device drivers, or OS-level components * Distributed storage, databases, or ... GPU programming (CUDA) or GPU systems experience * High-performance networking (RDMA, InfiniBand)

State Street Global Advisors

Platform Engineer

Toronto, ON · On-site

CA$90K - CA$157K/yr

As a Platform Engineer, you will be responsible for driving the architecture and implementation of ... Strong understanding ofLinuxfundamentals(networking, filesystems, kernel, isolation) * Ability to ...

Fivetran

Staff Software Engineer

Toronto, ON · Hybrid

Experience in systems-level engineering, including kernel, drivers, networking, or protocol analysis. * Experience working on developer infrastructure or highly reliable data platforms. This role ...

Omers

Lead, AI/Machine Learning Engineer

Toronto, ON

... Kernel. * Strong foundation in machine learning, including classical ML, such as scikit-learn, and ... Strong software engineering practices, including Git, code reviews, automated testing, and CI/CD ...

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Kernel Engineer information

What are the key skills and qualifications needed to thrive as a kernel engineer, and why are they important?

To thrive as a Kernel Engineer, you need deep expertise in C programming, operating system concepts, and low-level hardware interactions, typically supported by a degree in computer science or related fields. Familiarity with version control systems (like Git), debugging tools (such as GDB), and kernel development frameworks is crucial. Problem-solving, attention to detail, and effective communication are standout soft skills in this role. These skills enable the creation of reliable, efficient, and secure kernels that form the backbone of computing systems.

What is the difference between Kernel Engineer vs Device Driver Developer?

AspectKernel EngineerDevice Driver Developer
Required CredentialsBachelor's or higher in Computer Science, Linux/Unix knowledge, programming skills in C/C++Similar credentials, often with specialized knowledge in hardware and driver development
Work EnvironmentSystem-level development, kernel code, Linux/Unix environmentsHardware interaction, driver coding, embedded or OS-specific environments
Industry UsageOperating system development, open-source projects, hardware manufacturersHardware companies, embedded systems, OS vendors
Common Search/ComparisonKernel EngineerDevice Driver Developer

Kernel Engineers focus on developing and maintaining the core kernel of operating systems, ensuring system stability and performance. Device Driver Developers specialize in creating software that allows hardware components to communicate with the OS. While both roles require similar technical skills and often overlap, Kernel Engineers work on the entire kernel infrastructure, whereas Device Driver Developers concentrate on specific hardware interfaces.

What is a kernel engineer?

A Kernel Engineer is a software engineer who specializes in the development, maintenance, and optimization of operating system kernels, such as Linux or Windows. Their primary responsibilities include designing new kernel features, fixing bugs, improving performance, and ensuring compatibility with hardware. They often work closely with hardware manufacturers and other software developers to build stable and secure system foundations. Kernel Engineers must have a deep understanding of operating system internals, low-level programming (typically in C or C++), and computer architecture. This role is critical for maintaining and advancing the core components that allow computers and devices to function efficiently.

Are kernel engineers in demand?

Kernel engineers are in high demand due to the critical role they play in developing and maintaining operating system kernels, especially in areas like embedded systems, cybersecurity, and cloud computing. Companies seek professionals with expertise in C, C++, and Linux kernel development to improve system performance and security, making this a strong job market for qualified candidates.

What are some typical challenges kernel engineers face when working on operating system updates?

Kernel Engineers often encounter challenges related to maintaining system stability and compatibility when implementing updates or new features. Ensuring that changes do not introduce regressions or security vulnerabilities requires thorough testing and collaboration with QA and other engineering teams. Additionally, Kernel Engineers need to keep up-to-date with hardware advancements and support a wide range of devices, which can add complexity to their work. Effective communication and strong problem-solving skills are essential for navigating these challenges and delivering high-quality code.

What are popular job titles related to Kernel Engineer jobs in Ontario?

For Kernel Engineer jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Kernel Engineer jobs in Ontario look for?

The top searched job categories for Kernel Engineer jobs in Ontario are:

Kernel Engineer jobs near you
Infographic showing various Kernel Engineer job openings in Ontario as of August 2026, with employment types broken down into 90% Full Time, and 10% Contract. Highlights an 90% In-person, and 10% Remote job distribution.

Staff AI Platform & Agent Runtime Engineer

EQ Bank | Canada's Challenger Bank

Toronto, ON • On-site

Full-time

Re-posted 14 days ago

Job description

Purpose of the Job

We are looking for a Staff AI Platform & Agent Runtime Engineer to build the foundation for enterprise-scale AI and agent execution at EQ Bank. In this role, you will architect and operate the platform that powers our next generation of AI agents from experimentation through production, enabling teams across the organization to build, deploy, and scale intelligent agentic workloads securely and reliably. 


You will sit at the intersection of platform engineering, MLOps, and agentic AI, shaping the runtime, tooling, and developer experience that accelerates AI adoption across every business domain. This is a hands-on leadership role for someone who thrives on solving hard infrastructure problems and setting the technical direction for a rapidly evolving space. 

Main Activities:
Define enterprise AI platform architecture and roadmap. 
Design, build and operate AI-native CI/CD platforms. 
Implement secure-by-design AI controls and governance. 
Define reliability, observability, resilience and FinOps practices. 
Lead architecture reviews and developer enablement programs. 
Provide technical leadership across engineering teams. 
Knowledge/Skill Requirements:

   7+ years of software, platform, or cloud engineering experience, with 3+ years in AI/ML platforms or agentic AI systems. 
   Deep hands-on expertise with Azure (AKS, networking, private endpoints, identity, Key Vault) and Azure AI Foundry or equivalent AI platforms. 
   Proven experience building CI/CD pipelines for ML/LLM workloads (model, prompt, and agent lifecycle management). 
   Strong background in distributed systems, container orchestration (Kubernetes), and API/SDK design. 
   Experience with agent frameworks (e.g., Semantic Kernel, LangChain, AutoGen) and orchestration patterns (memory, tools, planning). 

   Solid understanding of LLM inference optimization, model routing, evaluation, and observability. 
   Track record of establishing platform standards, paved paths, and developer enablement at scale. 
   Excellent collaboration and communication skills across engineering, security, risk, and business stakeholders. 

Preferred Qualifications 

   Prior experience in regulated industries (financial services, banking, insurance). 
   Familiarity with Microsoft Fabric, Power Platform, Copilot, and Copilot Studio integrations. 
   Experience with FinOps for AI workloads including cost attribution, token accounting, and model economics. 
   Background in Responsible AI, model governance, and evaluation frameworks. 
   Contributions to open-source AI/agent platform projects.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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