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Edge Ai Machine Learning Jobs in Ontario (NOW HIRING)

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 ...

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 ...

Machine Learning Engineer

Toronto, ON · On-site

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 ...

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 ...

Deploy machine learning models on hardware platforms with a focus on edge AI and IoT systems. * Set up servers and deploy models to support production ML workloads. * Leverage containerization (e.g ...

New

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 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 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 ...

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 ...

Technology / AI / Semiconductor About the Role Our client is a global technology leader developing next-generation AI and machine learning solutions for mobile, automotive, IoT, and edge computing ...

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 ...

To achieve this, we've made significant investments in Advanced Analytics and AI capabilities. We are seeking an innovative and experienced Machine Learning Engineer to join our AI + Data team, a ...

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.

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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 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.

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 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 cities in Ontario are hiring for Edge Ai Machine Learning jobs?

Cities in Ontario with the most Edge Ai Machine Learning job openings:

Lead, AI/Machine Learning Engineer

Toronto, ON

Full-time

Retirement

Re-posted 3 days ago


Job description

Choose a workplace that empowers your impact.

Join a global workplace where employees thrive. One that embraces diversity of thought, expertise and experience. A place where you can personalize your employee journey to be - and deliver - your best.

We are a purpose-driven, dynamic and sustainable pension plan. An industry leading global investor with teams in Toronto to London, New York, Singapore, Sydney and other major cities across North America and Europe. We embody the values of our 665,000 members, placing their best interests at the heart of everything we do.

Join us to accelerate your growth & development, prioritize wellness, build connections, and support the communities where we live and work.

Don't just work anywhere - come build tomorrow together with us.

Know someone at OMERS or Oxford Properties? Great! If you're referred, have them submit your name through Workday first. Then, watch for a unique link in your email to apply.

The Lead, AI/Machine Learning Engineer will join the AI Delivery and Innovation team within the Platform Engineering, AI and Advanced Analytics department. This team acts as a central hub for AI capability at OMERS, partnering with Software Engineering, Customer Success and Innovation (CSI), and business areas to prototype, build, and ship AI solutions across Investments, Pension Services, Finance, and Corporate functions.

Reporting to the Associate Director, AI and ML, this role is hands-on across the full AI delivery lifecycle - from rapid prototyping and proof-of-concept development through to production-ready deployment. You will design and implement AI/ML and Generative AI solutions, operationalize them through robust engineering practices, and help shape how OMERS leverages AI to deliver measurable business outcomes. This is an opportunity to work at the intersection of cutting-edge AI, modern engineering, and real-world business problems in a collaborative, fast-paced environment.

You will be responsible for:

  • Designing and building end-to-end AI/ML and Generative AI solutions, including LLM applications, RAG pipelines, agentic workflows, and traditional ML models.

  • Building and maintaining MLOps/LLMOps/GenAIOps pipelines, including experiment tracking, model and prompt versioning, CI/CD, observability, drift detection, and automated retraining.

  • Building AI solutions using enterprise platforms, including Azure AI Foundry, Copilot Studio, and other approved AI platforms.

  • Working with vector databases, embeddings, and retrieval systems to ground LLMs on OMERS enterprise knowledge.

  • Conducting applied research on emerging models, agent frameworks, and AI engineering patterns, and translating findings into practical solutions and reusable components.

  • Collaborating with Software Engineering, Customer Success, and business stakeholders in an Agile environment to move initiatives from prototype to production and ensure successful adoption.

  • Contributing to AI governance, responsible AI practices, and architecture standards; embedding responsible AI principles and controls in everything you build.

  • Mentoring and coaching teammates through pairing, code reviews, and knowledge sharing; contributing to reusable skill, sub-agent, and component libraries to accelerate delivery.

  • Identifying, defining, and implementing improvements to existing engineering practices, tooling, and delivery processes while managing multiple initiatives and ensuring timely delivery.

Required Skills & Experience

  • 3+ years of professional software engineering experience, including 2+ years building and deploying production AI/ML or Generative AI solutions.

  • Hands-on experience with LLMs, including OpenAI, Anthropic, and open-source models; prompt engineering; RAG architectures; and fine-tuning.

  • Practical experience with one or more LLM/GenAI frameworks, such as LangChain, LlamaIndex, or Semantic Kernel.

  • Strong foundation in machine learning, including classical ML, such as scikit-learn, and deep learning, such as PyTorch or TensorFlow, with experience in feature engineering, model evaluation, and experimentation.

  • Experience implementing MLOps/LLMOps capabilities, including MLflow, Kubeflow, or equivalents; model registries; CI/CD for ML; observability, such as Arize, Langfuse, or similar; and drift monitoring.

  • Proven ability to design, build, and maintain production-grade services and full-stack applications that integrate AI capabilities.

  • Solid experience with cloud platforms, particularly Azure, including Azure AI Foundry and Azure OpenAI; working knowledge of GCP and Vertex AI is an asset.

  • Strong SQL skills and experience working with modern data platforms, including Databricks and Snowflake, and vector databases, including Azure AI Search, Pinecone, pgvector, or similar.

  • Demonstrated success delivering complex technical projects end-to-end, aligning expectations with various partners, and navigating ambiguity from prototype to production.

  • Strong software engineering practices, including Git, code reviews, automated testing, and CI/CD, with a bias toward shipping reliable, maintainable software.

  • Excellent communication skills, with the ability to explain technical concepts and trade-offs clearly to non-technical stakeholders and senior management.

  • Motivated to work in a collaborative environment with fast feedback, shared ownership of outcomes, and a focus on team success.

Preferred Skills & Experience

  • Experience with agent frameworks, such as Microsoft Agent Framework or Google ADK, and agentic workflows.

  • Experience containerizing workloads, including Docker and Container Applications, and deploying across cloud and on-premises GPU infrastructure.

  • Exposure to AI/ML observability and evaluation tooling beyond the core stack, and experience designing evaluation harnesses and guardrails for LLM-based applications.

  • Familiarity with responsible AI principles, governance frameworks, and enterprise architecture standards.

  • Experience in financial services, pensions, asset management, or related domains.

  • Bachelor's Degree in Computer Science, Engineering, Mathematics, or a related quantitative field; Master's degree is an asset, or equivalent work experience.

  • Experience mentoring engineers and contributing to communities of practice or reusable component libraries.

We believe that time together in the office is important for OMERS and Oxford, the strength of our employees, and the work we do for our pension members. In delivering on our pension promise, keeping us connected to our work and each other,our flexible hybrid work guideline requires teams to come in to the office 4 days per week.

This posting is for an existing vacancy.The expected salary range for this position is $86,000.00 - $130,000.00 per year.

You may also be eligible to receive an annual Incentive Award pursuant to our Short-term Incentive plan and our Long-Term Incentive plan (if applicable), and to participate in our group benefits and retirement plans - details on these elements of compensation are included within OMERS & Oxford offer letters.

As one of Canada's largest defined benefit pension plans, our people-first culture is at its best when our workforce reflects the communities where we live and work - and the members we proudly serve.

From hire to retire, we are an equal opportunity employer committed to an inclusive, barrier-free recruitment and selection process that extends all the way through your employee experience. This sense of belonging and connection is cultivated up, down and across our global organization thanks to our vast network of Employee Resource Groups with executive leader sponsorship, our Purpose@Work committee and employee recognition programs.

Artificial intelligence (AI) tools are used to support certain stages of the OMERS recruitment process. While AI assists us in our process, human judgment and decision-making remain central to our candidate experience.