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Research Assistant Deep Learning Jobs in Toronto, ON

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 products. * Work with large-scale, real-world datasets that range from banking transactions, to large ...

Quincus

Machine Learning Engineer

Toronto, ON

... latest research and techniques in deep learning and reinforcement learning. Qualifications ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Waabi

Research Engineer

Toronto, ON · On-site +1

CA$122K - CA$215K/yr

... deep learning, computer vision, and self-driving technologies to develop cutting-edge solutions ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Baycrest

Research Assistant Level 1 o 2

Toronto, ON

CA$39K - CA$54K/yr

The Research Assistant will support research conducted under the Canadian Consortium on ... Our salary ranges are structured to support progression, from learning the role to demonstrating ...

HeyGen

Research Engineer

Toronto, ON

Experience with deep learning frameworks such as PyTorch, and a capacity for quickly mastering new technologies. * A collaborative spirit with a proven track record in a team-based research or ...

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

... deep learning algorithms for virtual staining and digital pathology applications Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative ...

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

... deep learning algorithms for virtual staining and digital pathology applications Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative ...

Td

Machine Learning Engineer

Toronto, ON

CA$120K - CA$250K/yr

Our work spans the field of machine learning with areas such as deep learning and generative AI ... We are driven to be at the cutting edge of machine learning in research, engineering, and impactful ...

Td

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Our work spans the field of machine learning with areas such as deep learning and generative AI ... We are driven to be at the cutting edge of machine learning in research, engineering, and impactful ...

Td

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Our work spans the field of machine learning with areas such as deep learning and generative AI ... We are driven to be at the cutting edge of machine learning in research, engineering, and impactful ...

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All JobsResearch Deep Learning JobsResearch Assistant Deep Learning JobsResearch Assistant Deep Learning Jobs in Toronto, ON

Research Assistant Deep Learning information

What is the difference between Research Assistant Deep Learning vs Research Assistant Machine Learning?

AspectResearch Assistant Deep LearningResearch Assistant Machine Learning
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fields; knowledge of neural networksBachelor's or Master's in Computer Science, Data Science, or related fields; foundational ML knowledge
Work EnvironmentResearch labs, universities, tech companies focusing on AI and neural networksResearch labs, universities, tech companies working on various ML algorithms
Employer & Industry UsageAI research, deep learning projects, neural network developmentGeneral machine learning applications, data analysis, predictive modeling

Research Assistant Deep Learning specializes in neural networks and AI-focused projects, while Research Assistant Machine Learning covers a broader range of algorithms and data analysis tasks. Both roles require similar educational backgrounds but differ in technical focus and application areas.

What is a research assistant deep learning?

Research Assistant Deep Learning jobs involve supporting research projects focused on artificial intelligence, specifically within the field of deep learning. These roles typically require assisting with data collection, preprocessing, running machine learning experiments, and analyzing results. Research assistants may also help with literature reviews, code development, and documentation. The position is often found in academic, industry, or research lab settings, and usually requires a solid foundation in programming, mathematics, and neural network concepts.

What are the key skills and qualifications needed to thrive as a research assistant deep learning?

To thrive as a Research Assistant in Deep Learning, you need a strong background in machine learning, programming (especially Python), and a relevant degree in computer science or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, as well as experience with data preprocessing and GPU computing, are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills and qualities are essential for efficiently developing, testing, and improving advanced machine learning models in a fast-evolving field.

What does a research assistant deep learning do?

As a Research Assistant in Deep Learning, you can expect to work closely with research scientists and engineers to design, implement, and evaluate novel deep learning models. Typical daily tasks include data preprocessing, running experiments, analyzing results, and contributing to academic papers or presentations. You may also assist in developing codebases, conducting literature reviews, and collaborating with team members to solve technical challenges. The work environment is often collaborative and fast-paced, with opportunities to learn from experts and contribute to cutting-edge research projects.
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What job categories do people searching Research Assistant Deep Learning jobs in Toronto, ON look for? The top searched job categories for Research Assistant Deep Learning jobs in Toronto, ON are:
What cities near Toronto, ON are hiring for Research Assistant Deep Learning jobs? Cities near Toronto, ON with the most Research Assistant Deep Learning job openings:
Research Assistant Deep Learning jobs near you
Infographic showing various Research Assistant Deep Learning job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 28% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Research Scientist, Machine Learning (BioFM)

Deep Genomics

Toronto, ON

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 5 days ago

Job description

About Us


Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of RNA biology to identify novel drug targets, mechanisms, and therapeutics inaccessible through traditional methods. With expertise spanning machine learning, bioinformatics, data science, engineering, and drug development, our multidisciplinary team in Toronto and Cambridge, MA is revolutionizing how new medicines are created.

Opportunity


We are seeking an exceptional and creative Senior/Staff Machine Learning Scientist to lead and innovate within our core AI research team, specifically focusing on the creative building of Biological Foundation Models (BioFMs). You will pioneer novel deep learning architectures and pre-training paradigms that learn the fundamental language of the genome and cellular biology. Rather than just applying out-of-the-box ML to biological datasets, you will design the next generation of BioFMs from tackling complex -omics data at scale. If you are a first-principles thinker excited to bridge advanced ML with genome biology to solve high-impact, frontier problems in human health and drug discovery, this is a unique opportunity.


Key Responsibilities
  • Lead the creative research, architecture design, and training of Biological Foundation Models (BioFMs), on massive-scale genomic, transcriptomic, and single-cell datasets.
  • Collaborate closely with computational biologists and drug developers to integrate deep biological priors directly into model architectures and training objectives, ensuring our BioFMs capture fundamental and scientifically meaningful representations.
  • Rigorously implement, train, debug, and evaluate large-scale models to demonstrate scientific validity and drive progress on frontier problems in human health and genetic medicines.
  • Stay current with advancements in machine learning and computational biology research, identifying cross-disciplinary applications to solve real-world challenges.
  • Mentor junior scientists and engineers, fostering a culture of technical excellence and scientific curiosity through leadership and high-quality code review.
  • Share research findings through internal presentations and contribute to the scientific community via publications in top-tier venues.
Basic Qualifications
  • PhD (or evidence of equivalent level of expertise) with a strongly distinguished research focus in Computational Biology, Machine Learning, Computer Science, or a related quantitative field.
  • Deep understanding of modern deep learning and the creative building of foundation models, including CNNs, Transformers, and related sequence models (e.g., state-space models) specifically tailored for biological or genomic sequence data.
  • A demonstrated track record of building and scaling AI models for complex biological datasets (e.g., single-cell genomics, DNA/RNA sequences) from initial conception to production.
  • Proven ability to implement, train, and debug highly-performant deep learning models using frameworks like PyTorch.
  • Experience working with massive datasets and a deep understanding of the engineering and algorithmic challenges associated with scale.
  • Excellent communication skills, capable of discussing complex ideas seamlessly with both ML engineers and biological domain experts.
Preferred Qualifications
  • A strong track record of impactful research demonstrated through first-author publications in high-impact scientific journals (e.g., Nature, Science, Cell) or top-tier ML/CompBio conferences (e.g., NeurIPS, ICML, ICLR, ISMB, RECOMB).
  • 2+ years of relevant post-graduate experience at a leading industrial R&D lab or in a highly competitive academic environment building genomics AI.
  • Experience technically leading projects or mentoring junior researchers/engineers.
  • Proficiency with cloud computing platforms (e.g., GCP) for large-scale model training and experimentation.
  • Contributions to open-source projects demonstrating the ability to solve complex research problems in ML or computational biology.
What We Offer
  • A collaborative and innovative environment at the frontier of computational biology, machine learning, and drug discovery. 
  • Highly competitive compensation, including meaningful stock ownership.
  • Comprehensive benefits - including health, vision, and dental coverage for employees and families, employee and family assistance program. 
  • Flexible work environment - including flexible hours, extended long weekends, holiday shutdown, unlimited personal days.
  • Maternity and parental leave top-up coverage, as well as new parent paid time off. 
  • Focus on learning and growth for all employees - learning and development budget & lunch and learns.
  • Facilities located in the heart of Toronto - the epicenter of machine learning and AI research and development, and in Kendall Square, Cambridge, Mass. - a global center of biotechnology and life sciences.
Deep Genomics encourages applications from all backgrounds who seek the opportunity to build the world's leading AI-driven genetic medicine company. 
 
If you have a disability or special need, accommodation is available on request for candidates taking part in all aspects of the selection process.
 
 
*This posting reflects a current vacancy. 
 
We offer competitive compensation aligned with local market benchmarks. The salary range for this role is $175,000 - $200,000, and reflects Canada-based roles; compensation may differ for U.S.-based candidates.
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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