1

Hourly Embedded Machine Learning Jobs in Toronto, ON

Machine Learning Engineer

Toronto, ON · On-site

$118.80 - $148.50/hr

Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the ... Hourly team members get 15 days paid time off, with an additional day for each year of service

Embedded Engineer

Toronto, ON · Hybrid

$130K - $150K/yr

Embedded Engineer - Scientific Robotics & Automation Location: Flexible / Hybrid (in-office ... Machine learning or signal analysis * Predictive diagnostics * Data analysis and sensor readout ...

Embedded Software Test Engineer

Toronto, ON · Remote

CA$70K - CA$110K/yr

Machine Learning Test Developer Location: Markham ON Key Responsibilities * Test development for ... Embedded system testing (must have) * Excellent debugging and troubleshooting skills (must have)

Director, AI Solutions

Toronto, ON · On-site

$182 - $272/hr

Design and deploy generative AI and machine learning solutions embedded in CRM and customer workflows * Build systems including LLM‑powered copilots, agentic workflows, retrieval‑augmented ...

Experienced with computer vision algorithm development with strong understanding of machine learning algorithms and concepts * Experienced working with embedded system running RTOS/Linux and ...

... machine learning engineers, and full-stack builders to create intelligent agents used by millions of people every day. This is production-grade AI-deeply embedded into Workday's platform-not research ...

About Flinks Flinks is the embedded finance platform that brings together connectivity ... Machine Learning Platform Exposure: Experience supporting machine learning workflows, feature ...

Design and deploy generative AI and machine learning solutions embedded in CRM and customer workflows * Build systems including LLM-powered copilots, agentic workflows, retrieval-augmented generation ...

next page

Showing results 1-20

Hourly Embedded Machine Learning information

What are the key skills and qualifications needed to thrive as an Hourly Embedded Machine Learning Engineer, and why are they important?

To thrive as an Hourly Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

How does an Hourly Embedded Machine Learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What is an Hourly Embedded Machine Learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

What are the most commonly searched types of Embedded Machine Learning jobs in Toronto, ON? The most popular types of Embedded Machine Learning jobs in Toronto, ON are:
What job categories do people searching Hourly Embedded Machine Learning jobs in Toronto, ON look for? The top searched job categories for Hourly Embedded Machine Learning jobs in Toronto, ON are:
Staff Embedded Machine Learning Engineer (Open)

Staff Embedded Machine Learning Engineer (Open)

Nutanix

Markham, ON • On-site

$179.75 - $248.25/hr

Other

Posted 12 days ago


Job description

Company:Qualcomm Canada ULCJob Area:Engineering Group, Engineering Group > Machine Learning EngineeringGeneral Summary:We are seeking a Machine Learning software engineer with embedded experience.Qualcomm Automotive AI Software team is rapidly expanding to offer optimized solutions for infotainment and ADAS/Autonomous Driving. To scale and strengthen our offering in this domain, we are looking for a talented engineer to develop and deliver novel embedded AI solutions to enable state-of-the-art AI models on auto platforms for millions of end users. New Headcount.Key Responsibilities:Design and implement core components of the ML runtime framework for inference on embedded systems.Collaborate with compiler, hardware, and model teams to co-design efficient execution paths for AI workloads.Develop and maintain C++ code for runtime kernels and system-level integration.Develop tools to assist with performance profiling and debugging of quantized model accuracyAnalyze and improve runtime behavior using profiling tools and hardware counters.Support deployment of models from popular ML frameworks (e.g., Onnx, TensorFlow, PyTorch) onto Qualcomm’s inference stack.Challenging the status quo and driving innovations to be the best-of-class.Required Skills & Experience:Strong hands-on experience in performance optimization for embedded or low-power systems.Excellent in C++ programming , with a focus on system-level and runtime development.Solid understanding of embedded system design, including memory hierarchy and hardware-software interaction.Experience with Linux/Android/QNX development environments and toolchains.Familiarity with computer architecture, especially for AI accelerators or DSPs.Solid knowledge of machine learning concepts and model structures.Optimization of algebraic operations in algorithms for HW cores.Knowledge on deep learning and popular frameworks is an asset.Minimum Qualifications:Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.ORMaster's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.ORPhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.Pay range and Other Compensation & Benefits:$131,200.00 - $181,200.00The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer.If you would like more information about this role, please contact Qualcomm Careers . #J-18808-Ljbffr