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Embedded Ai Engineer Jobs in Ontario (NOW HIRING)

TTEC Digital seeks a Principal Software Engineer to join our team. This role is a full-time and ... ve embedded AI inside products, not just used it as a tool. Change doesn't rattle you; new ...

... internal teams building embedded AI experiences, and to a new generation of AI agents and ... Partner with engineering, security, and compliance leadership to make access governance a first ...

This role combines deep engineering execution with ownership of SDLC standards, policies, and frameworks, ensuring AI capabilities are embedded safely, consistently, and effectively across all stages ...

... internal teams building embedded AI experiences, and to a new generation of AI agents and ... Partner with engineering, security, and compliance leadership to make access governance a first ...

This role is Hybrid Ottawa AI Solutions Engineer Position Summary The AI Solutions Engineer will ... Software Engineering for Real-Time systems, Distributed Systems, embedded systems or mission ...

Staff Embedded Software Developer

Oshawa, ON · Hybrid

CA$147K - CA$196K/yr

AI Disclosure: As part of the application process, Artificial Intelligence will be used in the ... The Role We are looking for a skilled Staff Embedded Software Developer with a deep understanding ...

The engineer will build intelligent systems that bridge AI with enterprise software, industrial ... Embedded platforms * NVIDIA Jetson * GPUs * NPUs * Industrial edge platforms * Robotics platforms

Showing results 41-60

Embedded Ai Engineer information

What is an embedded AI engineer?

An Embedded AI Engineer is a professional who designs, develops, and implements artificial intelligence (AI) algorithms and models directly onto embedded systems, such as microcontrollers or edge devices. Their work involves optimizing AI solutions to run efficiently on hardware with limited computing resources, power, and memory. They collaborate with hardware engineers and software developers to integrate machine learning, computer vision, or other AI functionalities into products like smart appliances, autonomous vehicles, or IoT devices. Their expertise helps bring intelligent features directly to devices, enabling real-time decision-making without needing constant cloud connectivity.

What are the key skills and qualifications needed to thrive as an embedded AI engineer?

To thrive as an Embedded AI Engineer, you need expertise in embedded systems, AI/ML algorithms, programming languages like C/C++ and Python, and typically a degree in computer engineering or a related field. Familiarity with development tools such as TensorFlow Lite, ONNX, embedded Linux, and microcontroller platforms is essential, along with experience deploying AI models on resource-constrained devices. Strong problem-solving, collaboration, and communication skills help you work effectively in multidisciplinary teams and address real-world challenges. These skills ensure efficient integration of AI into embedded systems, enabling innovative, high-performance solutions for edge computing.

How does an embedded AI engineer typically collaborate with hardware and software teams during a project?

Embedded AI Engineers work closely with both hardware and software teams to ensure AI models are efficiently integrated into resource-constrained devices. They often collaborate with hardware engineers to optimize model performance based on device limitations like memory and processing power. At the same time, they coordinate with software developers to design efficient firmware and manage data pipelines. Regular cross-functional meetings and code reviews are common to address integration challenges and maintain alignment throughout the project lifecycle.

What is the difference between Embedded Ai Engineer vs Machine Learning Engineer?

CriteriaEmbedded Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Science, or related; knowledge of embedded systemsBachelor's or Master's in Computer Science, Data Science, or related; strong programming skills
Work EnvironmentEmbedded systems, IoT devices, hardware integrationData centers, cloud platforms, software development environments
Employer & Industry UsageConsumer electronics, automotive, IoT companiesTech firms, startups, research institutions
Common Search & ComparisonYesNo

Embedded Ai Engineers focus on integrating AI algorithms into embedded hardware and IoT devices, requiring knowledge of hardware constraints and embedded programming. Machine Learning Engineers develop models primarily for software applications and data analysis. While both roles involve AI, Embedded Ai Engineers specialize in hardware-software integration within embedded systems, whereas Machine Learning Engineers work on developing and deploying AI models in software environments.

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

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

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

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

Infographic showing various Embedded Ai Engineer job openings in Ontario as of August 2026, with employment types broken down into 71% Full Time, 25% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.

Senior Embedded Logging Software Developer

General Motors

Oshawa, ON • Hybrid

CA$115K - CA$164K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 28 days ago


Key responsibilities

  • Design, develop, and maintain embedded data pipelines and observability software across Android, Linux, and QNX platforms.

  • Build and extend libraries for configuration retrieval, validation, arbitration, and data transfer, ensuring reliable delivery under varying conditions.

  • Collaborate with cross-functional teams to deliver end-to-end data flows from ECU to cloud, including documentation and verification activities.


General Motors rating

8.2

Company rating: 8.2 out of 10

General Motors

Based on 308 frontline employees who took The Breakroom Quiz

7.3

Company rating compared to similar companies: 7.3 out of 10

Automakers average

Based on 6,327 frontline employees who took The Breakroom Quiz


Job description

Job Description

Vacancy Status:

This posting is for an existing vacancy within the organization and is open to new applications.

AI Disclosure:

As part of the application process, Artificial Intelligence will be used in the hiring process for this role

Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to the office three days per week, at minimum

The Role:

The Data Engineering organization at General Motors Canada is developing a unified, scalable Vehicle Observability Data Architecture to enable consistent, secure, and highfidelity data from vehicle ECUs to the cloud. We're seeking a Senior Embedded Logging Software Engineer to design and integrate embedded data pipelines across diverse invehicle platforms, ensuring cohesive interaction between the control plane (configuration, arbitration, lifecycle) and the data plane (streaming telemetry and filebased transfer).
The ideal candidate brings deep embedded expertise in C/C++ and Android, a track record of delivering solutions across Android Automotive, Linux, and QNX, and handson experience scaling observability data flows from ECU to cloud while meeting strict reliability, performance, and security requirements.

What You'll Do (Responsibilities)

  • Own and develop software solutions as part of a larger team; leading and participating in feature development, maintenance of existing features, and bug fixes

  • Lead and participate in code, and test case reviews

  • Conduct software verification (unit, and integration testing as needed)

  • Provide clear and complete documentation per the software development process

  • Collaborate with team members through Scrum/Agile

  • Take ownership of each project, make design and implementation decisions autonomously, and mentor junior members

  • Be an integral part of a new and energetic team


Embedded Observability Infrastructure

  • Define and implement observability SW across Android, Linux, and QNX

  • Support vehiclelocal data access mechanisms (e.g., USBbased retrieval) when connectivity is limited

Control Plane Integration

  • Build/extend Libraries to handle configuration retrieval, validation, arbitration, and persistence/fallback to lastknowngood

  • Define API contracts for library integrations

Data Plane Integration

  • Specify behaviors to ensure dependable delivery under varying connectivity and resource conditions.

Reliability, Performance & Security

  • Implement runtime controls to enable/disable observability data

  • Ensure compliance with cybersecurity and dataprotection requirements for local and remote access to observability data

Standards, Documentation & Collaboration

  • Produce clear design documents, configuration guides, and support operational runbooks

  • Collaborate closely with embedded platform teams, observability/data engineering, product, and validation to deliver endtoend data flows from ECU to cloud

Your Skills & Abilities (Required Qualifications)

  • Bachelor's degree in Computer Science, Engineering, or a related field.

  • 5+ years in embedded software development or systems engineering across Android, Linux, and/or QNX.

  • Strong coding proficiency in C/C++ and Android Java with experience in platformlevel integrations.

  • Experience designing metrics/telemetry for operational visibility and remote control at fleet scale.

  • Clear, concise technical communication; strong crossteam collaboration and design documentation skills.

What Can Give You a Competitive Advantage (Preferred Qualifications)

  • Experience integrating with control plane services (configuration retrieval, arbitration, persistence/fallback) and data plane pipelines (streaming and filebased transfer).

  • Experience developing SW Observability components

  • Experience designing driver/HMIinitiated capture flows (e.g., create/upload data).

  • Knowledge of automotive cybersecurity controls and dataprotection processes.

  • Exposure to OpenTelemetry, protobuf/gRPC, or similar observability/dataplane technologies.

  • Contributions to or strong affinity for opensource observability/logging ecosystems.

  • Automotive domain familiarity: ECU architectures, SoC platforms, diagnostics, failure/crash analysis

Compensation:

The salary range for this role is $115,000 to $164,600. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILLNEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE.

Benefits Overview

The goal of the General Motors of Canada total rewards program is to support the health and well-being of you and your family. Our comprehensive compensation plan currently includes the following benefits, in addition to many others:

  • Paid time off including vacation days, holidays, and supplemental benefits for pregnancy, parental and adoption leave;

  • Healthcare, dental, and vision benefits;

  • Life insurance plans to cover you and your family;

  • Company and matching contributions to a Defined Contribution Pension plan to help you save for retirement;

  • GM Vehicle Purchase Plan for you and your family.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Non-Discrimination and Equal Employment Opportunities

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.


Working at General Motors


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About General Motors

Sourced by ZipRecruiter

General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908