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Hourly Embedded Machine Learning Jobs in Toronto, ON

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our ... Working knowledge of embedded systems and their constraints * Sound software engineering practices ...

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our ... Working knowledge of embedded systems and their constraints * Sound software engineering practices ...

New

Embedded Software Test Engineer

Toronto, ON ยท 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)

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

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 ...

ML/AI Engineer

Toronto, ON ยท On-site +1

CA$110K - CA$150K/yr

... embedded in our clients' environments. At Levio, we valueexpertise, curiosity, and continuous ... The ML / AI Engineer design, build, deploy, and operate production-grade machine learning and ...

... embedded systems, and a multi-tenant cloud SaaS platform. This is a hands-on leadership position ... of LLMs and machine learning approaches, including their architectures, capabilities, and ...

Qualifications: - Pursuing PhD degree in Computer Science, Engineering, AI, Machine Learning ... The US hourly range for this role is: $60 USD and the Canada hourly range for this role is: $60-$65 ...

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Hourly Embedded Machine Learning information

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.

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 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.

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:

Machine Learning Engineer

Toronto, ON โ€ข Hybrid

Full-time

Medical, Dental

Posted 4 days ago


Job description

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our products to the next level in terms of visual intelligence.ย 

Our Companyย 

Invision AI is building a universal AI platform for computer vision applications. Powered by a unique multi-camera stack that generates high-integrity 3D digital twins of dynamic environments, our technology powers disruptive, market-leading solutions in intelligent infrastructure and globalย Transportation.ย 

The Role

As a Machine Learning Engineer, you will work across the full machine learning lifecycle, from data collection and labeling strategy through training, evaluation, deployment, monitoring, and ongoing improvement.

Your focus will be developing and maintaining computer vision models used in real-world products. While the work may involve researching and implementing new approaches, this is primarily an applied engineering position. We are looking for someone with a track record of building, shipping, and maintaining production ML systems.

The position includes working on projects that expand and strengthen our capabilities in object detection, image classification, geospatial tracking, and sensor fusion, with models deployed to resource-constrained edge devices.

Working within a collaborative team, you will build accurate, efficient, and principled solutions. As a key contributor to the company's next stage of growth, you will help advance our products, solve challenging customer problems, and shape our ML engineering practices in a fast-moving environment.

Location

This is a full-time, hybrid position based in Toronto. You will work from our downtown Toronto office three days per week.

What You'll Do

  • Recommend, develop, evaluate, and deploy ML models across our product lines
  • Build and improve data-labeling, training, and evaluation pipelines
  • Establish evaluation methods that connect model performance to product and business outcomes
  • Prototype new product capabilities using appropriate technologies
  • Optimize models for latency, memory usage, power consumption, and accuracy on edge devices
  • Diagnose and resolve issues affecting deployed models
  • Monitor production performance and identify model drift, data-quality problems, and retraining needs
  • Write maintainable, well-tested code and clear technical documentation
  • Participate in design reviews, code reviews, and technical planning
  • Share ML knowledge and collaborate with software, product, and other engineering teams

Requirements

Must Have

  • A track record of developing and deploying production computer vision models
  • Strong Python software development skills
  • Proficiency with frameworks such as PyTorch, TensorFlow and scikit-learn
  • Practical knowledge of CNNs and modern computer vision architectures
  • The ability to adapt open-source models to specific products and use cases
  • Hands-on work optimizing models for resource-constrained or edge environments
  • Knowledge of experiment tracking, dataset versioning, and ML observability
  • Skill in designing evaluation metrics that reflect product and business requirements
  • An understanding of model monitoring and production troubleshooting
  • Working knowledge of embedded systems and their constraints
  • Sound software engineering practices, including automated testing, code review, version control, and continuous integration
  • Strong written and verbal communication skills
  • Must be legally entitled to work in Canada

Bonus Skills

  • Familiarity with Docker or other container technologies
  • C++ development skills
  • GPU programming or performance-optimization knowledge
  • Knowledge of model compression techniques, including quantization, pruning, and knowledge distillation
  • Familiarity with edge inference tools such as ONNX Runtime, TensorRT
  • Familiarity with traditional, non-ML image-processing techniques
  • A background in sensor fusion or geospatial data

Benefits

  • A Mission that Matters: The opportunity to work on projects that make the world safer and greenerย 
  • Excellence: A culture of very high technical standards where quality engineering is valued over quick hacksย 
  • Technical Challenge: A wide variety of technology and tasks, including web development, distributed and edge computing, ML, real-time processing, and computer visionย 
  • Growth Environment: Join an international team where your voice is heard and your impact is visibleย 
  • Compensation and benefits: Competitive salary package including equity, allowing you to share in the success you help build. Benefits: RRSP Plan, Health and Dental and 4 weeks holiday.ย