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Hourly Embedded Machine Learning Jobs in Toronto, ON

Manager, Enterprise Analytics

Newmarket, ON · On-site

CA$69.20 - CA$82.26/hr

Permanent, Full timeNumber of Positions: 1Minimum - Maximum Hourly Rate: $69.20 - $82.26 Why Join ... Strong understanding of artificial intelligence, machine learning, predictive analytics, and ...

ML/AI Engineer

Toronto, ON · 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 ...

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 ...

Strong experience in development for Embedded Linux distributions; including kernel development * Knowledge of telematics systems and data visualization tools. * Familiarity with machine learning and ...

Develop and maintain data models across raw, refined, and curated layers to support reporting, embedded analytics, operational workflows, machine learning, and emerging AI use cases. * Build reliable ...

This senior role ensures that privacy and data protection requirements are embedded into systems ... Support privacy requirements for AI, machine learning, and advanced analytics use cases. * Ensure ...

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Hourly Embedded Machine Learning information

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.

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 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.

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:
Senior or Principal Software Development Engineer (Full Stack) - Agent Factory

Senior or Principal Software Development Engineer (Full Stack) - Agent Factory

Workday

Toronto, ON • On-site, Remote

Full-time

Re-posted 12 days ago


Workday rating

9.2

Company rating: 9.2 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

19th of 209 rated software companies


Job description

Your work days are brighter here.

We're obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you'll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We're in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you'll do meaningful work with Workmates who've got your back. In return, we'll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you've found a match in Workday, and we hope to be a match for you too.

About the Team

Agent Factory is where Workday's next chapter gets built. We're forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and full-stack builders to create intelligent agents used by millions of people every day. This is production-grade AI-deeply embedded into Workday's platform-not research experiments or maintenance work. Teams own problems end to end, collaborate tightly across disciplines, and use the right tools to solve real customer challenges at global scale. You'll work at the intersection of AI, platform architecture, and human workflows, with the autonomy to shape how agents reason, act, and scale responsibly. High trust, high expectations, and real impact. Engineering, but brighter.

About the Role

As a Senior or Principal Full Stack Software Engineer in Agent Factory, you'll help build the user-facing and platform experiences that bring Workday's AI agents to life. Working within a small, cross-functional pod, you'll design and ship full stack solutions-from intuitive front-end experiences to resilient backend services that integrate AI-driven capabilities deeply into HR and Finance workflows. This role is about turning powerful technology into products people actually use: scalable, reliable systems that simplify complex business processes for customers around the world. You'll collaborate closely with machine learning engineers, product managers, and platform teams, owning features end to end and seeing your work run in production. If you enjoy building real products, solving meaningful problems, and working with people who care about quality and craft, you'll feel right at home here.

Your responsibilities:

  • Build and deliver full stack features that power AI agents embedded in HR and Financial workflows

  • Own services and experiences from development through production-you build it, you run it

  • Collaborate in an iterative, team-first environment that values strong engineering practices and continuous learning

  • Share knowledge, mentor teammates, and help raise the technical bar across the pod

About You

Basic Qualifications | Senior Software Development Engineer

  • 8+ years of experience in software engineering

  • 5+ years experience with a web development framework (Python preferred: Flask, Django, or FastAPI)

  • 5+ years of experience with React and Typescript for Front End / Full stack development

  • 5+ years with a Relational DB (PostgreSQL preferred)

Basic Qualifications | Principal Software Development Engineer

  • 12+ years of experience in software engineering

  • 7+ years experience with a web development framework (Python preferred: Flask, Django, or FastAPI)

  • 7+ years of experience with React and Typescript for Front End / Full stack development

  • 7+ years with a Relational DB (PostgreSQL preferred)

Other Qualifications

  • Bachelor's degree in a computer related field or equivalent work experience

  • Experience building and operating SaaS products in cloud environments (AWS preferred)

  • Familiarity with the tradeoffs and architecture of modern distributed systems

  • Knowledge of software development best practices (DevOps, CI/CD, automated testing, observability)

  • Hands-on experience with containerization technologies (Docker, Kubernetes)

  • Exposure to additional programming languages like Java (backend) and TypeScript (frontend/fullstack) is a plus

  • Proven success working within fast-paced, agile environments and cross-functional teams

  • Strong communication skills, with the ability to collaborate with both technical and non-technical partners

  • Comfortable working with ambiguity and translating complex problems into clear, thoughtful solutions

  • Committed to fostering an inclusive, team-oriented environment and contributing to a culture of continuous improvement


Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.

Primary Location: USA.WA.SeattlePrimary Location Base Pay Range: $163,800 USD - $245,800 USDAdditional US Location(s) Base Pay Range: $148,200 USD - $264,000 USD


Our Approach to Flexible Work

With Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.


At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email accommodations@workday.com.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

At Workday, we value our candidates' privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.


What Workday employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Workday

Sourced by ZipRecruiter

Workday's journey began with a transformative idea generated during a breakfast conversation between its founders in sunny California. What set us apart from the start was our people-centric culture, driven by the core value of prioritizing our employees. At Workday, the happiness, growth, and contributions of every team member are at the heart of who we are. Our collaborative and employee-focused culture is the key ingredient for our business success. We not only care for our people but also for the communities and the environment, all while maintaining profitability. Embrace your uniqueness, as we encourage our Workmates to shine brightly in their authentic selves. Our passion and energy make us distinct, and we are inspired to create a brighter workday for everyone.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

Pleasanton, CA, US

Year founded

2005