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Full Time Meta Machine Learning Jobs in Toronto, ON

Waabi

Research Engineer

Toronto, ON · On-site +1

CA$122K - CA$215K/yr

Qualifications: - Bachelor's in computer science, engineering, machine learning, or a related ... full-time employees only). - Unlimited Vacation. - Flexible hours and Work from Home support ...

Waabi

Senior / Staff Perception Engineer

Toronto, ON

CA$158K - CA$269K/yr

... machine learning, computer vision, and self-driving technologies, and apply insights from the ... full-time employees only). - Unlimited Vacation. - Flexible hours and Work from Home support ...

Owl.co

Principal Software Engineer

Toronto, ON

CA$220K - CA$300K/yr

Deep, hands-on experience designing, deploying, and scaling AI/Machine Learning systems or LLM ... Our technical leadership comes from Meta, Microsoft, X, and Goldman Sachs, bringing world-class ...

Waabi

Research Scientist, Learnable Planner

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

Qualifications: - MS/PhD degree in Computer Science, AI, Machine Learning, Computer Vision ... full-time employees only). - Unlimited Vacation. - Flexible hours and Work from Home support ...

Waabi

Research Scientist

Toronto, ON

CA$158K - CA$269K/yr

Qualifications: - Masters/PhD degree in Computer Science, AI, Machine Learning, Computer Vision ... full-time employees only). - Unlimited Vacation. - Flexible hours and Work from Home support ...

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All JobsMeta Machine Learning JobsFull Time Meta Machine Learning JobsFull Time Meta Machine Learning Jobs in Toronto, ON

Full Time Meta Machine Learning information

What is the difference between Full Time Meta Machine Learning vs Data Scientist?

AspectFull Time Meta Machine LearningData Scientist
Required CredentialsBachelor's or Master's in CS, ML, or related fields; experience with ML frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentTech company, collaborative teams, focus on ML modelsVaried industries, research or business focus, data analysis
Industry UsagePrimarily in tech giants like Meta, Google, focus on AI/ML productsAcross industries including tech, finance, healthcare, often in analytics roles

Full Time Meta Machine Learning roles focus on developing and deploying machine learning models within Meta's ecosystem, requiring specialized ML skills. Data Scientists analyze data to generate insights, often using statistical methods. While both roles involve data and algorithms, Meta Machine Learning positions are more specialized in AI/ML model development, whereas Data Scientists focus on data analysis and interpretation across various industries.

What are the most commonly searched types of Meta Machine Learning jobs in Toronto, ON? The most popular types of Meta Machine Learning jobs in Toronto, ON are:
Full Time Meta Machine Learning jobs near you
Infographic showing various Full Time Meta Machine Learning job openings in Toronto, ON as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Senior / Staff Machine Learning Infrastructure Engineer

Waabi

Toronto, ON • On-site, Remote

CA$157K - CA$234K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 22 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will..
- Design, develop, and implement the machine learning platform for the continuous deployment and integration of machine learning models.
- Collaborate with data scientists and engineers to understand model requirements and optimize pipeline processes.
- Automate the training, testing and deployment processes for machine learning models.
- Continuously monitor and maintain model pipelines, ensuring optimal performance, accuracy and reliability.
- Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.
- Ensure compliance with security and data privacy standards in all MLOps activities.
 
Qualifications:
- 3-5 years of experience supporting machine learning training platforms.
- Bachelor's degree in Computer Science, Data Science or a related field.
- Strong understanding of machine learning principles and model lifecycle management.
- Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow or PyTorch.
- Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services.
- Experience managing technology such as JupyterHub and Kubeflow.
- Familiarity with containerization and orchestration tools such as Kubernetes and Docker.
- Strong problem-solving skills and ability to troubleshoot complex issues.
- Experience with monitoring tools and practices for model performance in production.
- Ability to work collaboratively in cross-functional teams.
 
Bonus/nice to have: 
- Experience with infrastructure-as-code (IaC) tools such as Terraform or Crossplane.
- Knowledge of big data technologies like Apache Spark or Hadoop.
- Familiarity with data engineering practices and tools.
- Experience with A/B testing and model validation in production environments.
- Relevant MLOps certifications (e.g., AWS Certified Machine Learning - Specialty, DataRobot MLOps Certification) are a plus.
The US yearly salary range for this role is: $157,000 - $234,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.'s yearly salary ranges are determined based on several factors in accordance with the Company's compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations.  Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve! 

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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