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New Grad Machine Learning Jobs in Ontario (NOW HIRING)

$110 - $170/hr

For new-grad applicants, at least one first author publication in top machine learning / data mining conferences including ICML, NeurIPS, ICLR, KDD, CIKM, ICDM, SDM, The Web Conference, etc.

New

$167.53 - $249.96/hr

For new-grad applicants, at least one first author publication in top machine learning / data mining conferences including ICML, NeurIPS, ICLR, KDD, CIKM, ICDM, SDM, The Web Conference, etc.

... 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 ...

Machine Learning Engineer

Toronto, ON · Hybrid

CA$152K - CA$174K/yr

A proven ability to quickly learn new technologies and adapt to a dynamic, fast-paced environment ... machine learning expert; * Exceptional communication skills and the ability to build trust with ...

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, 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 ...

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 ...

Machine Learning Engineer II

Toronto, ON · On-site

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 ...

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 ...

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 ...

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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:
Infographic showing various New Grad Machine Learning job openings in Ontario as of July 2026, with employment types broken down into 1% Internship, 88% Full Time, 10% Part Time, and 1% Contract. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution.

Machine Learning Research Engineer

Socket.dev

On-site

$110 - $170/hr

Other

Posted 3 days ago

New


Job description

The Product Operations machine learning team is seeking a machine learning research engineer to conduct research in anomaly detection and automated machine learning to address domain-specific challenges in manufacturing multi-modal data that includes time-series, graph, image and/or tabular data. Research engineers on our team drive projects from ideation to validation, with the goal of improving our core manufacturing ML capabilities. They support ML software engineers in translating successful approaches to production code, and train MLEs to apply them to factory use cases.

DESCRIPTION

The Apple Operations team ensures that ground breaking designs become industry-leading products. In this role you will join a small team at the heart of our manufacturing ML capabilities. Our R&D team is responsible for the core ML libraries that engineers use to train models for factory deployment. We improve core capabilities through applied research, with partners in academia and across Apple's research org.

MINIMUM QUALIFICATIONS
  • Expertise in independently designing and implementing ML experiments - establishing appropriate metrics, benchmarks, milestones, and communicating results to stakeholders with varying levels of technical background Ph.D. in Machine Learning from CS or ECE Publication record commensurate with seniority
PREFERRED QUALIFICATIONS
  • Track record of successful research and interest in one or more of the following: weakly- and semi-supervised machine learning, domain adaptation, data efficiency, knowledge distillation, imbalanced classification and regression, tabular foundation models, etc.
  • For new-grad applicants, at least one first author publication in top machine learning / data mining conferences including ICML, NeurIPS, ICLR, KDD, CIKM, ICDM, SDM, The Web Conference, etc.
  • Excellent communication and presentation skills
  • Demonstrable collaborative software development skills, including design review and code review
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