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Algorithm Research Jobs in Toronto, ON (NOW HIRING)

Quincus

Machine Learning Engineer

Toronto, ON

Quincus Research is building the next generation of intelligent systems for all Quincus products ... algorithms at scale. As a machine learning engineer, you will be responsible for designing and ...

NTENT

Machine Learning Engineer

Toronto, ON · On-site

$80 - $120/hr

Design tests for machine learning algorithm effectiveness and performance monitoring. * Design tools and interfaces for interactive machine learning and teaching. * Research and development on ...

NTENT

Machine Learning Engineer

Toronto, ON · Remote

Design tests for machine learning algorithm effectiveness and performance monitoring. * Design tools and interfaces for interactive machine learning and teaching. * Research and development on ...

Amazon

Applied Scientist III, RBKS AI

Toronto, ON

This role offers a unique opportunity to shape next-generation home security technology while advancing the field of AI algorithms and systems. The team is focused on productizing research in ...

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

... algorithm performance, validate research hypotheses, and drive iterative improvements Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative ...

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

... algorithm performance, validate research hypotheses, and drive iterative improvements Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative ...

Chubb

Senior Data Scientist

Toronto, ON

... and algorithmic solutions. Build analytical solutions for complex P&C claims operations ... Research, recommend, and implement AI methodologies appropriate for the given risk assessment ...

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All JobsAlgorithm Research JobsAlgorithm Research Jobs in Toronto, ON

Algorithm Research information

Is ML a high paying job?

Machine Learning (ML) roles, including those in algorithm research, are generally well-paid due to the high demand for specialized skills in data analysis, programming, and statistical modeling. Salaries vary based on experience, location, and industry, but advanced ML positions often offer competitive compensation compared to other tech roles.

What is algorithmic research?

Algorithm research involves studying and developing new algorithms to solve computational problems efficiently. It requires understanding theoretical concepts, analyzing algorithm performance, and often involves programming and testing in environments like Python or C++. This work supports advancements in fields such as artificial intelligence, data analysis, and software development.

What are the key skills and qualifications needed to thrive as an Algorithm Researcher, and why are they important?

To excel as an Algorithm Researcher, you need a strong background in mathematics, computer science, and algorithm design, often supported by an advanced degree such as a master's or PhD. Proficiency with programming languages (like Python, C++, or Java), machine learning frameworks, and version control systems is essential. Analytical thinking, creativity, and effective communication are crucial soft skills that set top performers apart in this field. These skills are vital for developing innovative, efficient solutions and collaborating within interdisciplinary teams to solve complex computational problems.

Which 3 jobs will survive AI?

Algorithm research jobs are likely to persist because they involve developing new algorithms and understanding complex data, tasks that require human creativity and critical thinking. Roles in healthcare, such as medical professionals, and skilled trades like electricians or plumbers, are also expected to remain in demand due to the need for hands-on expertise and human judgment. These jobs often require specialized knowledge, certifications, or physical skills that are difficult for AI to replicate fully.

Is AI replacing algorithms?

Algorithm research involves developing and improving algorithms, which are fundamental to AI systems. AI often relies on algorithms to process data and make decisions, but it does not replace the need for algorithm development; instead, AI advances can lead to new algorithmic techniques and improvements. Researchers in this field focus on creating efficient, effective algorithms that support AI applications and other computational tasks.

What is Algorithm Research?

Algorithm research involves studying, designing, analyzing, and optimizing algorithms to solve complex problems efficiently. Researchers in this field explore new computational methods, improve existing algorithms, and evaluate their performance in various contexts. This work is fundamental in areas like computer science, artificial intelligence, data science, and cryptography, driving technological advances and innovation.

What are the typical challenges faced by professionals in Algorithm Research roles and how can they best address them?

Algorithm Research professionals often encounter challenges such as bridging the gap between theoretical solutions and practical implementation, staying updated with rapid advancements in the field, and collaborating with cross-functional teams to integrate research outcomes into real-world products. To address these challenges, it is helpful to maintain strong communication with engineering teams, participate in continual learning through academic papers and conferences, and adopt an iterative approach to testing and refining algorithms. Building a habit of documenting experiments and results also streamlines collaboration and future development.

What is the difference between Algorithm Research vs Data Scientist?

AspectAlgorithm ResearchData Scientist
Required CredentialsAdvanced degrees in CS, Mathematics, or related fieldsDegree in CS, Statistics, or related fields; certifications like SAS or Python
Work EnvironmentResearch labs, R&D departments, academiaBusiness environments, analytics teams, tech companies
Industry UsageDeveloping new algorithms, theoretical researchAnalyzing data, building predictive models, insights generation
Common Search/ComparisonYesNo

Algorithm Research focuses on developing and testing new algorithms, often in research or academic settings, requiring advanced technical credentials. Data Scientists analyze data to generate insights and build models, working primarily in business environments. While both roles involve data and programming, their core objectives and work settings differ significantly.

Algorithm Research jobs near you
Infographic showing various Algorithm Research job openings in Toronto, ON as of July 2026, with employment types broken down into 4% Locum Tenens, 63% Full Time, 23% Part Time, 3% Contract, 6% Nights, and 1% Summer. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution.

Machine Learning Engineer

Quincus

Toronto, ON

Full-time

Re-posted 7 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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