research-scientist

Student Union is the Waikato Students' Union (WSU), a student-led, campus-based organization that represents and supports University of Waikato students. It provides advocacy, student support services, clubs and events, campus facilities and bookings, and runs local hubs on the Hamilton and Tauranga campuses. The union operates as a non-profit body focused on student welfare, campus life, and amplifying student voices through elections, committees and partnerships with university services.

As the campus-wide programming board at Wake Forest University, Student Union offers more than 200 programs throughout the year including Springfest, Homecoming,campus traditions, coffeehouses, special events,  films, and trivia.

Student Union

• Conduct research related to peer-support and professional development matters
• Work in co-operation with the peer support and equity-based services
• Review workplace policies and best practices

Administrative Research Assistant

Research Assistant conducting research related to peer-support and professional development at McMaster Students Union. Responsible for reviewing workplace policies and working with equity-based services.

Waabi is a company at the forefront of autonomous trucking technology. Led by AI and self-driving pioneer Raquel Urtasun, Waabi uses advanced Generative AI to develop scalable and safe self-driving solutions. The Waabi Driver, their cutting-edge product, blends an end-to-end trained AI stack with an interpretable architecture, facilitating OEM integration and large-scale commercialization. Waabi World, their highly advanced simulation engine, offers a realistic and immersive environment that accelerates the development and deployment of self-driving technology by reducing the reliance on extensive real-world testing. With partnerships and a visionary approach, Waabi aims to revolutionize logistics and supply chain industries.

Waabi, founded by AI pioneer and visionary Raquel Urtasun, is an AI company building the next generation of self-driving technology. With a world class team and an innovative approach that unleashes the power of AI to “drive” safely in the real world, Waabi is bringing the promise of self-driving closer to commercialization than ever before. Waabi is backed by best-in-class investors across the technology, logistics and the Canadian innovation ecosystem, including Khosla Ventures, Uber, 8VC, Radical Ventures, OMERS Ventures and BDC Capital’s Women in Technology Venture Fund. 
To learn more visit: waabi.ai
Press: press@waabi.ai
Business: partnership@waabi.ai

Waabi

• Conduct fundamental and applied research in generative and predictive world-modeling
• Video generation and prediction.
• Latent diffusion / autoregressive / flow-matching models.
• Multimodal foundation models for driving scenes.
• LLM / VLM / VLA methods for scene understanding, reasoning, and control.
• Generative scenario modeling and controllable simulation.
• Model distillation.
• Collaborate with engineers to integrate models into large-scale, distributed training and rendering pipelines.
• Publish high-impact research at top conferences (CVPR, ECCV, ICCV, NeurIPS, ICLR, ICRA, SIGGRAPH).
• Mentor junior scientists and interns; foster a culture of scientific rigor and rapid experimentation.
• Stay on top of emerging advances in generative AI, differentiable rendering, knowledge distillation/compression, and robotics.

Research Scientist, World Models

Research Scientist focusing on developing algorithms and productionizing World Models at Waabi. Join a startup pioneering autonomous transportation technology with a world-class team.

Engineering Society of Queen's University is a student-led organization dedicated to supporting engineering students through various clubs, conferences, competitions, and academic resources. The society provides professional development opportunities, wellness support, and organizes events that foster collaboration and innovation within the engineering community at Queen's University.

Formed in 1897, the Engineering Society of Queen’s University is one of the oldest representative bodies for engineering students in Canada and continues to be a leader in student initiatives. With over 3,600 members currently staying on campus, 15,000 active alumni living worldwide, and an annual budget of $2.4 million, the Engineering Society oversees some fifty-eight student-run initiatives ranging from design projects to services to student events.

Engineering Society of Queen's University

• Design and execute computational models, including sequence analysis, protein modeling, and structural prediction.
• Develop computational pipelines using Python, R, AlphaFold, machine learning, and bioinformatics tools.
• Analyze wet lab data to generate predictive models that inform experimental design and project direction.
• Create compelling visualizations, figures, and simulations for technical summaries and presentations.
• Document modeling approaches, code, scripts, and datasets to ensure reproducibility.
• Collaborate directly with the wet lab, human practices, and website teams to integrate and communicate computational findings.

Computational Biology Research Assistant

Computational Biology Research Assistant at QGEM developing computational models and pipelines. Responsibilities include analyzing wet lab data and collaborating with interdisciplinary teams.

ShyftLabs is a company that specializes in delivering data and AI solutions to enterprises. They offer a range of services, including consulting, prototyping, solutions, platform scaling, and operations to help businesses navigate their data journey and leverage AI for transformative impact. ShyftLabs focuses on empowering organizations with advanced data analytics, AI capabilities, and secure data infrastructure to drive real value and optimize operations across the enterprise. They partner with clients throughout the entire lifecycle of data and AI needs, ensuring efficient and impactful integration of AI solutions into existing workflows. With expertise in cloud platform services and a commitment to secure, optimal performance, ShyftLabs delivers tailored solutions for strategic data and AI transformation.

Empowering organizations to take a data-first approach to decision making. Establish processes to make faster, insightful decisions to help you stay above the competition.

ShyftLabs

• Conduct applied research to solve real-world problems using LLMs, graph-based models, and multimodal AI.
• Rapidly understand problem context, constraints, and success metrics, and design pragmatic AI solutions aligned with product and business goals.
• Design hybrid AI architectures combining knowledge graphs, vector search, and deep learning for reasoning-aware systems.
• Research and implement graph embeddings, graph attention networks (GATs), and graph neural networks (GNNs) for representation learning and inference.
• Design and build advanced RAG systems at scale, going beyond naïve vector similarity search.
• Implement hybrid semantic retrieval across vector stores and graph databases (e.g., entity-aware retrieval, path-based reasoning, graph-augmented RAG).
• Optimize retrieval pipelines for latency, relevance, grounding, and explainability in production environments.
• Fine-tune LLMs and embedding models for domain-specific tasks (instruction tuning, adapters, LoRA, etc.).
• Design and implement LLM agent systems, including multi-agent orchestration strategies, tool use, planning, and memory.
• Evaluate, iterate, and optimize agent architectures to solve complex, multi-step enterprise workflows efficiently.
• Build and fine-tune document extraction pipelines, including (OCR systems, Layout-aware models, Vision-Language Models (VLMs), Multimodal document understanding and classification).
• Design scalable pipelines for enterprise document ingestion, enrichment, indexing, and retrieval.
• Build end-to-end AI pipelines covering data ingestion, feature engineering, training, evaluation, deployment, and monitoring.
• Partner with platform and data engineering teams to productionize solutions on AWS or GCP.
• Monitor model performance, detect drift, and drive continuous improvement strategies.
• Design evaluation frameworks, offline metrics, and online experimentation (A/B testing) to measure real-world impact.

Applied Scientist

Applied Scientist leveraging applied research to design production AI systems for Fortune 500 companies. Focusing on knowledge-centric AI, graph-based learning, and advanced RAG architectures.

We, of Enactus Bow Valley, believe that everyone deserves a chance to develop their future and choose the path they lead. Through hand-ups over hand-outs, Enactus Bow Valley College members are strengthening themselves as professionals and philanthropists while empowering their communities.

Enactus at Bow Valley College

• Assist Faculty with a literature review
• Receive training and guidance from Faculty
• Undertake research-specific professional skill development training

Student Research Assistant

Student Research Assistant assisting Faculty with literature reviews and skill development training at Bow Valley College. Requires current enrollment as a student at Bow Valley College.

At TELUS, our purpose-driven team works together every day to innovate and do good. From providing technology solutions that make our lives safer and easier, to supporting those who need it most, our inclusive, spirited and giving people are passionate about empowering our customers, communities and each other to thrive in our digital world. 

A company that helps you be your best self at home and at work:
Find a place where you truly belong, your opinions are valued and you can be your best self.

A career that ignites your full potential:
Get the guidance and support you need to explore your interests, build your skills and get where you want to go.

A culture that goes beyond the expected to strengthen communities and the planet:
Seize the opportunity to make a difference in our communities and do good for our planet as part of our purpose-driven team.

An innovative team committed to solving complex, real world problems:
Join a digitally-enabled workforce that’s pushing the boundaries to create sustainable change.

Join us, and let’s make the future friendly, together www.telus.com/careers

TELUS

• Lead the iterative development, validation, and deployment of AI and machine learning models across the organization, ensuring continuous improvement and scalability
• Lead the development and deployment of generative AI applications, tools, and frameworks to solve critical problems
• Contribute to end-to-end automation efforts required for productionizing machine learning models, ensuring smooth deployment and operationalization
• Work with structured and unstructured data to design, develop, and deploy innovative predictive models, metrics, and dashboards that deliver actionable insights
• Present results creatively in various formats (e.g., dashboards, interactive reports) so insights are easily understood and actionable for stakeholders at all levels
• Influence strategic decision-making and promote organization-wide data-driven adoption by solving business challenges and uncovering new opportunities
• Develop reusable code and solutions to accelerate future goals and deliver results with increased speed and reliability
• Support the evolution of data science and AI solutions by influencing product roadmaps, prioritizing features that meet business needs, and recommending the latest research, tools, and industry best practices
• Build and maintain strong engagement with key stakeholders, understand their priorities and business needs, and present AI and machine learning initiatives to vice-presidential and senior leadership
• Act as a functional leader for AI and machine learning across the enterprise, provide technical leadership for the overall AI and ML program, and collaborate with other business units to deploy AI and ML solutions
• Establish best practices for deploying and operating machine learning models, ensuring models are scalable, reliable, and optimized for long-term success
• Represent the company and position it as a leading authority in AI and machine learning by presenting at conferences, publishing articles, and participating in external forums to build TELUS’s reputation as a global leader in data science and AI
• Provide coaching and mentorship to a growing team of engineers and data scientists, foster a culture of continuous learning and innovation, and identify future leaders within the organization

Senior Scientist, AI & Machine Learning

Lead the AI and machine learning initiatives at TELUS to drive data-driven decision making. Collaborate with various teams for innovative data solutions and insights.

Cohere is a leading AI platform providing enterprises with advanced language models and an integrated workspace designed for efficiency and security. With a family of high-performance generative and retrieval models, Cohere enables organizations to streamline workflows, enhance data security, and unlock insights across various industries through multilingual capabilities. Their focus on customized AI solutions ensures the protection of critical data while facilitating seamless integration into existing organizational processes.

Cohere is the leading data security-focused enterprise AI company. It is a global technology company co-headquartered in Toronto and San Francisco, with key offices in London and New York. The company builds enterprise-grade frontier AI models with industry-leading multilingual capabilities designed to solve real-world business challenges. Cohere’s AI solutions are cloud-agnostic to meet companies wherever their data is stored and offer the highest levels of security, privacy, and customization with on-premises and private cloud deployment options. 

Cohere

• Create ambitious new evaluation benchmarks that push the limits of what our models can accomplish.
• Work on highly cross-functional teams to translate model feedback into trustworthy, repeatable evaluations.
• Conduct research to advance the state-of-the-art in LLM evaluation methods, including training LLM judges; refining LLM-based data synthesis pipelines; and improving evaluation efficiency.
• Build scalable and reusable tools for digging into model performance.

Senior Research Scientist, Model Evaluation

Senior Research Scientist creating evaluation methods and benchmarks for LLMs at Cohere. Working with cross-functional teams to advance AI capabilities and model performance evaluation.

Hybrid Research Scientists roles in Canada

Browse 7 hybrid research scientists roles hiring in Canada plus related opportunities such as research engineer, data scientist, ai research scientist and clinical research.

7 jobs found