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Senior Embedded Machine Learning Jobs in Toronto, ON

Td

Research Machine Learning Scientist

Toronto, ON

CA$140K - CA$250K/yr

... senior levels, and will evaluate your application in its entirety. Layer 6 is the AI research ... We develop and deploy industry-leading machine learning systems that impact the lives of over 27 ...

Sage Recruiting

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 ...

EvenUp

Staff Machine Learning Engineer

Toronto, ON · Remote

$212K - $301K/yr

Join EvenUp as a Staff Machine Learning Engineer and help set the technical direction for how ... senior engineers, and driving decisions that shape both product outcomes and company growth. What ...

Accenture

Oracle Data Reporting Lead

Toronto, ON · On-site

An Oracle Data and Reporting Lead (Senior Manager) providing executive-level leadership for ... Advise on the use of Oracle's embedded AI and machine learning capabilities within Oracle Cloud ...

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Senior Embedded Machine Learning information

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

What are some common challenges faced by senior embedded machine learning engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What are the key skills and qualifications needed to thrive as a senior embedded machine learning engineer?

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What does a senior embedded machine learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.
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:
Senior Embedded Machine Learning jobs near you
Infographic showing various Senior Embedded Machine Learning job openings in Toronto, ON as of June 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution.

Junior Machine Learning Engineer

Socket.dev

Hamilton, ON • On-site

$55 - $75/hr

Other

Medical, Dental, Vision, PTO

This job post has expired today. Applications are no longer accepted.

Job description

### // About Providius

Providius has been at the forefront of innovation in the Media & Entertainment industry for over a decade, delivering solutions to complex challenges in IP media and IT infrastructure within mission-critical environments.

Headquartered in Hamilton, Ontario, Canada, we are a privately held company focused on building practical, reliable systems that solve real-world problems.

### // What We’re Looking For

We’re looking for a junior machine learning engineer to join our team and grow into a strong, hands-on ML engineer.

This is a role for someone early in their career who is eager to learn, comfortable getting their hands dirty with real data, and motivated to build a solid foundation in applied machine learning.

You will work under the direction of senior ML and engineering staff, contributing to real models and pipelines while developing your skills and judgment over time.

### // Position Overview

Working closely with senior engineers, you will:

  • implement, train, and evaluate models under guidance
  • prepare and explore real-world data
  • help build and maintain data pipelines
  • support experiments and document results
  • This role is hands-on and engineering-focused.

You will be writing code, working with messy, real-world data, and learning how machine learning systems are built and run in practice.

Over time, as you build experience, you will take on more ownership and tackle increasingly open-ended problems.

### // Duties and Responsibilities

  • Implement and train models under the guidance of senior engineers
  • Prepare, clean, and explore datasets, including feature engineering
  • Run experiments, record results, and help interpret findings
  • Build and maintain parts of the data pipeline and supporting tooling
  • Help integrate models into larger systems alongside the team
  • Write clear, testable, and maintainable code
  • Ask good questions, seek feedback, and learn from code review

### Requirements

### // Required Skills / Experience

  • 0–2 years of experience in machine learning, or strong academic or project experience
  • Programming ability in Python
  • Solid grounding in machine learning fundamentals
  • Willingness to work with real-world, imperfect data
  • Strong problem-solving ability and a desire to learn
  • Ability to take direction and incorporate feedback
  • Clear communication in a team environment

### // What this Role Requires

  • Eagerness to learn and grow quickly
  • Comfort working with guidance and asking for help when needed
  • Pragmatism and a willingness to see tasks through
  • Attention to detail and care in the work
  • Ownership of your own learning and contributions

### // Nice to haves

  • Coursework, internships, or projects involving anomaly detection, time-series, or behavioral modeling
  • Exposure to streaming or telemetry data
  • Familiarity with common ML libraries and tooling
  • Experience contributing to a shared codebase

### // Why join Providius

  • Own a product area with real autonomy and direct impact
  • Work on products that operate in real-time, high-stakes environments
  • Small team with high ownership and a direct line to leadership

### Benefits

### Benefits

  • Dental care
  • Extended health care
  • On-site parking
  • Paid time off
  • Vision care
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