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Machine Learning Engineer New Grad Jobs in Toronto, ON

Quincus

Machine Learning Engineer

Toronto, ON

... new projects and focuses that meet the demands of the world's fast-paced business needs. Job ... As a machine learning engineer, you will be responsible for designing and implementing scalable ...

NTENT

Machine Learning Engineer

Toronto, ON · Remote

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 ...

Clio

Machine Learning Engineer

Toronto, ON · Hybrid

CA$129K - CA$174K/yr

A proven ability to quickly learn new technologies and adapt to a dynamic, fast-paced environment ... machine learning engineer. This posting is for an existing vacancy. What you will find here:

Td

Machine Learning Engineer

Toronto, ON · On-site

CA$120K - CA$250K/yr

As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an ... Grow by continuously learning new skills and exploring advanced topics in AI with a team that ...

Bree

Machine Learning Engineer

Toronto, ON · On-site

$100 - $130/hr

Apply machine learning design patterns to build modular, reusable, and production-ready models. * Collaborate with data engineers to develop high-performance data pipelines for training and inference.

Providius

Junior Machine Learning Engineer

Hamilton, ON · On-site

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 ...

BDO Canada

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$84K - CA$128K/yr

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

BDO Canada

Senior Machine Learning Engineer

Oakville, ON · On-site

CA$84K - CA$128K/yr

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

Td

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$170K - CA$250K/yr

As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an ... Grow by continuously learning new skills and exploring advanced topics in AI with a team that ...

Stripe

Machine Learning Engineer

Toronto, ON · Remote

... new business opportunities. Our mission is to increase the GDP of the internet, and we have a ... What you'll do As a machine learning engineer, you will be responsible for analyzing opportunities ...

TheAppLabb

Sr. Machine Learning Engineer

Toronto, ON · On-site

We are looking for a Sr. Machine Learning Engineer to help translate raw data into meaningful insights that drive strategic decision-making. The Opportunity Summary We are seeking an experienced ...

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Machine Learning Engineer New Grad information

What is a machine learning engineer new grad?

A Machine Learning Engineer New Grad job is an entry-level role for recent graduates specializing in machine learning and artificial intelligence. It typically involves developing, training, and deploying machine learning models, working with large datasets, and optimizing algorithms for performance. New grads in this role often collaborate with data scientists, software engineers, and product teams to integrate models into applications. Employers look for proficiency in programming (Python, TensorFlow, PyTorch), a strong foundation in ML concepts, and experience with data processing. This role provides an opportunity to gain hands-on industry experience and grow technical skills in real-world applications.

What are the key skills and qualifications needed to thrive in the machine learning engineer new grad position, and why are they important?

To thrive as a Machine Learning Engineer New Grad, a strong background in computer science, statistics, and mathematics, often supported by a relevant degree, is essential. Familiarity with programming languages like Python or Java, machine learning frameworks (such as TensorFlow or PyTorch), and basic knowledge of data tools and cloud platforms is typically required. Effective problem-solving, eagerness to learn, and clear communication help new grads excel when collaborating on projects and learning from senior team members. These skills and qualities are vital for adapting quickly, contributing to team goals, and building a successful foundation in this fast-evolving technical field.

What are the typical day-to-day tasks of a machine learning engineer new grad?

As a Machine Learning Engineer New Grad, your daily tasks often include collecting and preprocessing data, developing and testing machine learning models, and analyzing model performance. You may work closely with data scientists and software engineers to integrate models into production systems and address real-world business problems. Participating in team meetings, code reviews, and collaborative projects is common, providing opportunities to learn best practices and receive mentorship. This hands-on, varied workload helps you quickly build technical and collaborative skills early in your career.

What are popular job titles related to Machine Learning Engineer New Grad jobs in Toronto, ON?

For Machine Learning Engineer New Grad jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer New Grad jobs in Toronto, ON look for?

The top searched job categories for Machine Learning Engineer New Grad jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Machine Learning Engineer New Grad jobs?

Cities near Toronto, ON with the most Machine Learning Engineer New Grad job openings:

Machine Learning Engineer New Grad jobs near you
Infographic showing various Machine Learning Engineer New Grad job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer

Quincus

Toronto, ON

Full-time

Re-posted 12 days ago

Job description

"Make every logistics journey your best one yet"

The Company.
Founded in 2014, Quincus is a B2B supply chain operating SaaS platform headquartered in Singapore. We solve today's global supply chain challenges with groundbreaking technology. Using AI and machine learning, we have digitized and optimized the logistics process while giving customers full transparency into their supply chain. 
 
Quincus was founded by two visionary entrepreneurs who possess more than a decade of experience in tech. Chief Product Officer Katherina-Olivia Lacey is leading a tech revolution in this space while empowering women in the supply chain industry. Jonathan E. Savoir, Chief Executive Officer, appeared on Forbes' 30 Under 30 Asia List in 2020, and also serves on the boards of several startups.  

Overview.
Quincus Research is building the next generation of intelligent systems for all Quincus products. To achieve this, we're working on projects that utilize the latest computer science techniques developed by skilled software engineers and research scientists. Quincus Research teams collaborate closely with other teams across Quincus, maintaining the flexibility and versatility required to adapt new projects and focuses that meet the demands of the world's fast-paced business needs. 

Job Overview. 
We are looking for a highly motivated and experienced machine learning engineer to join our team and help us develop and deploy deep learning and reinforcement learning algorithms at scale. As a machine learning engineer, you will be responsible for designing and implementing scalable systems for serving models, optimizing inference performance, and managing production workflows. 

Responsibilities: 
- Design and implement scalable systems for serving deep learning and reinforcement learning models.
- Optimize inference performance of deep learning and reinforcement learning models using techniques such as quantization, pruning, and distillation.
- Utilize GPU computing to accelerate model training and inference.
- Develop and deploy production workflows for training and serving machine learning models.
- Collaborate with data scientists and software engineers to design and implement machine learning systems.
- Monitor and improve the performance of machine learning models in production.
- Stay up-to-date with the latest research and techniques in deep learning and reinforcement learning. 
 
Qualifications:
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
- 3+ years of experience in software engineering or machine learning engineering.
- Strong programming skills in Python (C++ or Java a plus)
- Experience with deep learning frameworks such as TensorFlow or PyTorch.
- Experience with GPU programming using CUDA, OpenCL, or similar libraries.
- Experience with distributed systems and cloud computing platforms such as Kubernetes, Docker, GCP, and AWS. 

Preferred Qualifications: 
- Ph.D. in Computer Science, Electrical Engineering, or a related field.
- 5+ years of experience in software engineering or machine learning engineering.
- Experience with reinforcement learning algorithms and frameworks.
- Experience with production deployment of machine learning models and implementation of APIs for big data.
- Strong understanding of computer architecture and performance optimization.
- Strong communication and collaboration skills. 

If you are passionate about developing and deploying machine learning algorithms at scale, and want to join a dynamic team working on cutting-edge technology, we encourage you to apply for this position.
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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