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Edge Ai Machine Learning Jobs in Ontario (NOW HIRING)

NTENT

Machine Learning Engineer

Toronto, ON · Remote

Research and development on cutting-edge machine learning technologies. Qualifications and Skills: * Graduate degree in Computer Science with a strong background in machine learning required.

Machina Labs

Machine Learning Engineer

Chatsworth, ON · On-site

CA$160K - CA$190K/yr

Stay current with the latest developments in machine learning and AI and evaluate their applicability to our manufacturing challenges. * Write clean, well-documented, and production-quality Python ...

Td

Machine Learning Engineer II

Toronto, ON

CA$154K - CA$199K/yr

We are looking for world-class engineers to tackle cutting-edge problems in Machine Learning applied to the real world. Our team is building standardized frameworks to launch AI models that have real ...

Clio

Machine Learning Engineer

Toronto, ON · Hybrid

CA$129K - CA$174K/yr

Clio is the global leader in legal AI technology, empowering legal professionals and law firms of ... Summary: We are currently seeking a Machine Learning Engineer to join our rapidly growing ...

Themis

Machine Learning Engineer

Mississauga, ON · On-site

CA$85K - CA$135K/yr

Machine Learning Engineer About Themis Intelligence Themis Intelligence builds the Utility ... We work at the frontier of applied AI, building models and data systems that integrate time-series ...

Royal Bank of Canada

Lead AI Engineer

Toronto, ON · On-site

We are looking to hire a talented Data & AI Engineer to build cutting edge AI and data solutions ... Expertise in Generative AI and Machine Learning service integrations. Familiar with Gen AI tech ...

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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.
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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

NTENT

Toronto, ON • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 21 days ago

Job description

Machine Learning Engineer
Position: Full time
Location: Toronto, Ontario (Initially Remote)
About Us:
NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search technologies directly into their business-to-consumer offerings. We are a unique group of brilliant minds intent on discovering, learning and building. We work in a vibrant atmosphere, with an emphasis on personal and professional development. This is an opportunity to tackle complex problems usually reserved for a handful of large companies in the search industry.
About the Opportunity:
We are looking for a talented Machine Learning Engineer to join our team and deliver machine learning-driven products. The right candidate will work on development, deployment, and lifecycle management of machine learning models for various large-scale applications (natural language understanding, web search and ranking, recommendation, personalization, dialog/conversation management).
Keywords:
Machine learning, natural language processing, learning-to-rank, online learning, deep learning, interactive machine learning, machine teaching, conversational agents, human computer interaction
Duties and Responsibilities:
  • Design, implement, and deploy machine learning algorithms.
  • Manage machine learning algorithm lifecycle.
  • Coordinate data collection and annotation efforts.
  • Work with real-time data and content coming from various data sources.
  • Manage machine learning data pipelines.
  • Design tests for machine learning algorithm effectiveness and performance monitoring.
  • Design tools and interfaces for interactive machine learning and teaching.
  • Research and development on cutting-edge machine learning technologies.
Qualifications and Skills:
  • Graduate degree in Computer Science with a strong background in machine learning required.
  • Strong problem-solving abilities, solid background in algorithms and data structures required.
  • Strong programming skills in Python and Scala required. Experience in other programming languages (eg. Java, R, Haskell) a plus.
  • Solid knowledge of machine learning tools (eg. scikit-learn, tensorflow, keras, pytorch, Spark MLlib) required.
  • Experience with distributed and streaming data technologies (eg. Hadoop, Spark, Kafka) required.
  • Experience with building and deploying API's with Docker and Kubernetes required.
  • Experience with natural processing tasks (eg. named entity recognition, language modeling, vector representations) required.
  • Experience with Elastic Search, Lucene a plus but not required.
  • Experience with ranking algorithms a plus but not required.
  • Experience with interactive machine learning (eg. active learning, reinforcement learning, machine teaching) a plus but not required.
The ideal candidate will be self-motivated, possess excellent communication skills (both oral and written) and be able to work independently. A keen interest in various aspects of natural language processing is essential in our multi-disciplinary team.
We offer a full comprehensive benefits package including medical, dental and vision. Employees receive a generous time off (PTO) plan and 13 holidays per year. We also offer 401(k) benefits, long term disability benefits and life.

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