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Edge Ai Machine Learning Jobs in Ontario (NOW HIRING)

onsemi

Machine Learning Engineer, Edge AI

Waterloo, ON · On-site

CA$120K - CA$170K/yr

We are looking for a Machine Learning Engineer, Edge AI to lead the integration and control of our next-generation AI accelerators. As our products evolve to include dedicated neural network hardware ...

Omers

Lead, AI/Machine Learning Engineer

Toronto, ON · On-site

  • Retirement

The Lead, AI/Machine Learning Engineer will join the AI Delivery and Innovation team within the ... This is an opportunity to work at the intersection of cutting-edge AI, modern engineering, and real ...

Thri5 Inc.

AI / Machine Learning Engineer

Toronto, ON · On-site

Your Role As an AI / Machine Learning Engineer at Thri5, you'll help build the agent layer that powers our System of Actions. You'll design and implement multi-agent Co-pilot systems that orchestrate ...

Tenstorrent

CA$100K - CA$500K/yr

The ML Models team sits at the intersection of cutting-edge AI research and high-performance hardware, bringing state-of-the-art machine learning models to life on Tenstorrent's custom AI ...

Td

Machine Learning Engineer

Toronto, ON

CA$120K - CA$250K/yr

Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge * Architect scalable machine learning and Gen AI systems that integrate with existing ...

Quincus

Machine Learning Engineer

Toronto, ON · On-site

Using AI and machine learning, we have digitized and optimized the logistics process while giving ... cutting-edge technology, we encourage you to apply for this position. We may use artificial ...

Numerator

Numerator is looking for a hands-on Tech Lead Manager to join our growing Machine Learning team ... Manage and grow a small team of AI software engineers -- 1:1s, career development, performance ...

Numerator

Numerator is looking for a hands-on Tech Lead Manager to join our growing Machine Learning team ... Manage and grow a small team of AI software engineers -- 1:1s, career development, performance ...

Boson AI

Machine Learning Engineer - Enterprise

Toronto, ON · On-site

CA$150K - CA$400K/yr

Driven by a passion for cutting-edge AI research, particularly in the transformative areas of large ... We are seeking a skilled, detail-oriented, and passionate Machine Learning Engineer to join our ...

Td

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$170K - CA$250K/yr

Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge * Architect scalable machine learning and Gen AI systems that integrate with existing ...

Td

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge * Build scalable machine learning frameworks across multiple delivery teams where ...

Td

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge * Build scalable machine learning frameworks across multiple delivery teams where ...

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Edge Ai Machine Learning information

What is an Edge AI Machine Learning?

An Edge AI Machine Learning job involves developing and deploying machine learning models directly on edge devices, such as IoT sensors, mobile devices, and embedded systems. This role requires expertise in optimizing AI models for low-power, low-latency environments while ensuring real-time processing. Professionals in this field work with frameworks like TensorFlow Lite, ONNX, and OpenVINO to implement AI solutions efficiently. They must also handle challenges like model compression, hardware acceleration, and data privacy.

What are some typical challenges faced in an Edge AI Machine Learning role, and how can I prepare for them?

One of the most common challenges in Edge AI Machine Learning is optimizing models to run efficiently on hardware with limited resources, while maintaining acceptable accuracy and speed. You may encounter constraints related to memory, processing power, and connectivity, which require creative engineering and a deep understanding of both machine learning and embedded systems. Collaborating closely with hardware engineers, data scientists, and software developers is typical, as solutions often span multiple technical disciplines. To prepare, staying current with advancements in model compression, quantization, and edge deployment technologies will help you tackle these challenges with confidence.

What are the key skills and qualifications needed to thrive in the Edge AI Machine Learning position?

To thrive as an Edge AI Machine Learning professional, you need a strong background in machine learning algorithms, embedded systems, and proficiency with programming languages such as Python or C++. Familiarity with edge computing platforms (like NVIDIA Jetson, Google Coral), frameworks (TensorFlow Lite, ONNX), and certifications in AI or ML can greatly enhance your qualifications. Strong problem-solving abilities, collaboration, and effective communication skills are important for adapting solutions to diverse environments and working cross-functionally. These abilities enable the successful deployment of efficient and robust AI models directly on devices, meeting the unique challenges of real-time, resource-constrained settings.

How to become an edge AI machine learning engineer?

To become an edge AI machine learning engineer, develop strong skills in machine learning, embedded systems, and programming languages like Python and C++. Gain experience with hardware platforms such as NVIDIA Jetson or Raspberry Pi, and learn to optimize models for low-power, resource-constrained environments. Earning certifications in AI, embedded systems, or IoT can also enhance your qualifications.
What are popular job titles related to Edge Ai Machine Learning jobs in Ontario? For Edge Ai Machine Learning jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Edge Ai Machine Learning jobs in Ontario look for? The top searched job categories for Edge Ai Machine Learning jobs in Ontario are:
What cities in Ontario are hiring for Edge Ai Machine Learning jobs? Cities in Ontario with the most Edge Ai Machine Learning job openings:
Edge Ai Machine Learning jobs near you

Machine Learning Engineer, Edge AI

onsemi

Waterloo, ON • On-site

CA$120K - CA$170K/yr

Full-time

Re-posted 25 days ago

Onsemi rating

8.3

Company rating: 8.3 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

Job description

We are looking for a Machine Learning Engineer, Edge AI to lead the integration and control of our next-generation AI accelerators. As our products evolve to include dedicated neural network hardware, the challenge shifts from pure algorithm implementation to complex hardware orchestration.

This role is about more than just writing kernels; it's about defining the firmware layer that sits between high-level AI frameworks and our custom silicon. You will be responsible for how our DSPs manage, schedule, and feed data to these accelerators. We need a veteran who can look at a PyTorch model and determine the best way to tile memory, manage DMA transfers, and synchronize processing to ensure we hit our ultra-low-power targets while maximizing throughput. You will also be the primary technical voice influencing our future hardware specs to ensure our accelerators are actually "firmware-friendly."

onsemi (Nasdaq: ON) is driving disruptive innovations to help build a better future. With a focus on automotive and industrial end-markets, the company is accelerating change in megatrends such as vehicle electrification and safety, sustainable energy grids, industrial automation, and 5G and cloud infrastructure. With a highly differentiated and innovative product portfolio, onsemi creates intelligent power and sensing technologies that solve the world's most complex challenges and leads the way in creating a safer, cleaner, and smarter world.

More details about our company benefits can be found here:

https://www.onsemi.com/careers/career-benefits

We are committed to sourcing, attracting, and hiring high-performance innovators, while providing all candidates a positive recruitment experience that builds our brand as a great place to work.


onsemi is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, ancestry, national origin, age, marital status, pregnancy, sex, sexual orientation, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, or any other protected category under applicable federal, state, or local laws.

If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact Talent.acquisition@onsemi.com for assistance.

What You'll Need

  • Strong Python, PyTorch and ONNX experience developing, training, evaluating, and deploying machine learning models.
  • Deep understanding of modern AI architectures including CNNs, Transformers, state-space models, and other emerging neural network approaches.
  • Experience optimizing, deploying and debugging models across a wide spectrum of edge devices, from ultra-constrained microcontrollers and DSPs to high-performance AI accelerators and GPUs.
  • Experience developing machine learning solutions for one or more sensing domains, including time-series signals, audio, computer vision, or ultrasonic sensing.
  • Hands-on experience with model compression and deployment techniques such as quantization, pruning, graph optimization, and operator/kernel optimization.
  • Practical experience translating research concepts into production-quality systems.
  • Strong understanding of model performance tradeoffs involving latency, memory footprint, power consumption, and accuracy.
  • 4+ years of industry and/or academic experience in machine learning research, model development, or AI systems engineering.

Nice to Have

  • CUDA development and GPU optimization experience.
  • Experience with TensorRT, ONNX Runtime, TVN, IREE, or similar inference frameworks.
  • Experience with TinyML, embedded inference runtimes, or DSP programming.
  • Familiarity with multimodal AI systems.

onsemi is excited to share the base salary range for this position i$120,000 - $170,000 exclusive of fringe benefits or potential bonuses.The final pay rate for the successful candidate will depend on geographic location, skills, education, experience, and/or consideration of internal equity of our current team members. We also offer a competitive benefits package

What You Will Do

  • Lead research and development efforts in edge AI and embedded machine learning.
  • Design, train, evaluate, optimize, and deploy machine learning models spanning applications from low-power 1D sensor processing through high-dimensional sensing systems such as ultrasonic arrays.
  • Investigate and develop novel architectures for constrained edge deployments, balancing performance, power, latency, and memory requirements.
  • Optimize AI workloads through techniques such as quantization, pruning, graph optimization, kernel acceleration, and hardware-aware training.
  • Deploy models across a variety of hardware platforms, including onsemi solutions and third-party edge AI hardware.
  • Stay current with advances in machine learning research and translate promising techniques into scalable, production-ready products.
  • Work closely with hardware, firmware, and software teams to co-design AI solutions that maximize efficiency, performance, and scalability on resource-constrained edge platforms

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