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New Grad Machine Learning Jobs in Ontario (NOW HIRING)

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 ...

Magna

Machine Learning Engineer

Milton, ON · On-site

The Machine Learning Engineer will play a pivotal role in driving innovation and operational ... and benchmark of new / existing smart factory ML solutions measures at other Magna plants or ...

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 ...

IXL Learning

Software Developer, New Grad

Toronto, ON

CA$90K - CA$92K/yr

IXL Learning, developer of personalized learning products used by millions of people globally, is ... As a Software Developer, New Grad on our Integrations team, you will design and develop the tools ...

Priceline

Senior Machine Learning Developer

Toronto, ON · Hybrid

CA$155K - CA$180K/yr

Have the opportunity to design new machine learning models and build new machine learning products in a small but growing team within a large organization. Work at a company where the business is ...

Hays

Remote Length : 6 month contract (long term potential) Your New Company Our client is a fast-paced, product-led business building advanced machine learning capabilities to drive smarter customer ...

Td

Senior Machine Learning Engineer

Toronto, ON

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 ...

StackAdapt

Applied Machine Learning Scientist

London, ON · On-site +1

We are searching for a talented Applied Machine Learning Scientist to join our engineering team as ... This ranges from creating entirely new algorithms, to improvements on state-of-the art methods, to ...

Td

Research Machine Learning Scientist

Toronto, ON

CA$140K - CA$250K/yr

Research, develop, and apply new techniques in deep learning to advance our industry leading ... Proven track record of applying machine learning to solve real-world problems ...

Td

Machine Learning Engineer II

Toronto, ON

CA$154K - CA$199K/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 ...

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All JobsNew Grad Machine Learning JobsNew Grad Machine Learning Jobs in Ontario

New Grad Machine Learning information

What are some typical challenges new graduates might face when starting out in a machine learning role, and how can they overcome them?

New grad machine learning engineers often encounter challenges such as bridging the gap between academic knowledge and practical, production-level projects. Adapting to real-world data issues, collaborating with cross-functional teams, and understanding scalable deployment can be daunting at first. To overcome these, it's helpful to seek mentorship, proactively ask questions, and dedicate time to learning best practices in code versioning, model evaluation, and team communication. Engaging in code reviews and participating in team discussions can also accelerate the learning curve and foster professional growth.

What are the key skills and qualifications needed to thrive as a New Grad Machine Learning Engineer, and why are they important?

To thrive as a New Grad Machine Learning Engineer, you need a solid foundation in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, version control systems like Git, and coursework or certification in data science are highly beneficial. Strong problem-solving abilities, curiosity, and effective communication skills help you collaborate and convey complex technical concepts to diverse teams. These skills and qualities are essential for developing innovative models, ensuring project success, and integrating seamlessly into fast-paced tech environments.

What is the difference between New Grad Machine Learning vs Data Scientist?

AspectNew Grad Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some internshipsBachelor's or Master's in CS, Statistics, or related; some experience
Work EnvironmentEntry-level, team-focused, research and developmentData analysis, modeling, cross-functional collaboration
Employer & Industry UsageTech companies, startups, research labsTech, finance, healthcare, consulting firms

New Grad Machine Learning roles typically focus on foundational skills, internships, and entry-level tasks, while Data Scientist positions often require more experience in data analysis and statistical modeling. Both roles are common in tech industries, but Data Scientists usually handle broader data analysis responsibilities.

What are 'New Grad Machine Learning' roles?

New Grad Machine Learning roles are entry-level positions designed for recent graduates who have studied machine learning, artificial intelligence, data science, or related fields. These positions typically involve working with experienced data scientists and engineers to develop, implement, and improve machine learning models and algorithms. New grads in these roles often contribute to projects involving data preprocessing, model training, evaluation, and deployment. The goal is to help new graduates gain hands-on experience and grow their skills in a real-world setting while contributing to the organization's AI initiatives.
What are popular job titles related to New Grad Machine Learning jobs in Ontario? For New Grad Machine Learning jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching New Grad Machine Learning jobs in Ontario look for? The top searched job categories for New Grad Machine Learning jobs in Ontario are:
What cities in Ontario are hiring for New Grad Machine Learning jobs? Cities in Ontario with the most New Grad Machine Learning job openings:
New Grad Machine Learning jobs near you

Machine Learning Engineer

Quincus

Toronto, ON

Full-time

Posted 16 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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