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Research Assistant Deep Learning Jobs in Toronto, ON

Waabi

Research Scientist, Learnable Planner

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

You will... - Design and execute on a research agenda for deep-learning based motion planning for ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Synechron

Sr. GenAI Engineer

Toronto, ON · Hybrid

CA$130K - CA$145K/yr

Research & Stay Updated:Keep abreast of advancements in deep learning, NLP, and AI methodologies to continuously improve the platform and solutions. Requirements: * PhD or Master's degree in Computer ...

NTENT

Machine Learning Engineer

Toronto, ON · Remote

Machine learning, natural language processing, learning-to-rank, online learning, deep learning ... Research and development on cutting-edge machine learning technologies. Qualifications and Skills:

Waabi

Senior / Staff Perception Engineer

Toronto, ON

CA$158K - CA$269K/yr

... research insights, leveraging your expertise in deep learning, computer vision, and self-driving ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

OpenSpace

Sr. Computer Vision Engineer

Toronto, ON

CA$168K - CA$220K/yr

You will leverage classical CV, deep learning (transformers, multi-modal models), and probabilistic ... Collaborate with platform engineers to transition research prototypes into production-ready ...

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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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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.

Research Scientist, Learnable Planner

Waabi

Toronto, ON • On-site, Remote

CA$158K - CA$269K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 16 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

The Motion Planning team delivers the core module within the autonomy stack that makes decisions and generates trajectories for our self-driving trucks. As a research scientist working on Learnable Planner, you will invent new AI technologies that support scalable planning solutions enabling our launch of fully driverless autonomous trucks. You will contribute towards Waabi's vision of a single AI system that learns end-to-end and in a provably safe manner as well as our revolutionary high-fidelity, closed-loop simulator, Waabi World.
 
You will...
- Design and execute on a research agenda for deep-learning based motion planning for self-driving.
- Leverage and advance the state-of-the-art in robotics and machine learning to enable safe self-driving at scale, with advanced techniques in imitation and reinforcement learning, planning and search, perception and prediction, simulation, foundation models and more.
- Support deploying solutions to our production systems, collaborating closely with platform teams to ensure seamless integration of research findings into production systems.
- Stay up-to-date and advance beyond the state-of-the-art in artificial intelligence, machine learning, computer vision, and self-driving technologies.
- Champion engineering excellence, ensuring high-quality, well structured and tested code.
- Submit and publish work externally at top machine learning, computer vision, and robotics conferences (NeurIPS, ICLR, ICML, CVPR, etc.) and post to our company blog.
 
Qualifications:
- MS/PhD degree in Computer Science, AI, Machine Learning, Computer Vision, Robotics and/or similar technical field(s) of study. Exceptional Bachelor's students will also be considered.
- Experience in planning/decision making approaches (e.g., imitation learning, reinforcement learning, optimal control, optimization based approaches, search methods, probabilistic decision making).
- Demonstrated research experience through previous internships, work experience, research projects, and papers at top conferences.
- Strong quantitative background and coursework in or working knowledge of linear algebra, calculus, and probability.
- Proficient in reading and coding in Python.
- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
 
Bonus/nice to have:
- Previous experience in self-driving technology. 
- Experience deploying ML/DL models to a production motion planning or related robotics stack.
- Proficiency in Pytorch, Rust, C++ and/or CUDA.
The US yearly salary range for this role is: $158,000 - $269,000 USD in addition to competitive perks & benefits. Waabi US Inc.'s yearly salary ranges are determined based on several factors in accordance with the Company's compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve! 

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.
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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