Ottawa, ON · On-site
CA$239.47/hr
Modern techniques such as fine-tuning, parameter-efficient training, in-context learning, contrastive learning, retrieval-augmented generation (RAG), and multi-agent systems for enabling complex ...
Ottawa, ON · On-site
CA$239.47/hr
Modern techniques such as fine-tuning, parameter-efficient training, in-context learning, contrastive learning, retrieval-augmented generation (RAG), and multi-agent systems for enabling complex ...
CA$67K - CA$124K/yr
Design and build enterprise AI applications that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and workflow automation to improve business processes.
CA$67K - CA$124K/yr
Design and build enterprise AI applications that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and workflow automation to improve business processes.
Toronto, ON · Hybrid
CA$130K - CA$145K/yr
Lead the design and development of innovative machine learning architectures involving zero-shot/few-shot learning, retrieval-augmented generation (RAG), embeddings, and neural networks.
Toronto, ON · Hybrid
CA$130K - CA$145K/yr
Lead the design and development of innovative machine learning architectures involving zero-shot/few-shot learning, retrieval-augmented generation (RAG), embeddings, and neural networks.
Leading the design of generative and agentic AI solutions, including prompting, retrieval augmented generation, tool use and multi-step agent workflows, and the techniques needed to make them ...
Leading the design of generative and agentic AI solutions, including prompting, retrieval augmented generation, tool use and multi-step agent workflows, and the techniques needed to make them ...
Toronto, ON · On-site
CA$70/hr
... Retrieval-Augmented Generation (RAG) architectures Strong understanding of vector embeddings, semantic search and prompt engineering Experience working with PostgreSQL and pgvector Google Cloud ...
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Toronto, ON · On-site
CA$70/hr
... Retrieval-Augmented Generation (RAG) architectures Strong understanding of vector embeddings, semantic search and prompt engineering Experience working with PostgreSQL and pgvector Google Cloud ...
Ottawa, ON · Hybrid
CA$106K - CA$118K/yr
Design data architectures that support AI-ready data access, including structured knowledge bases, contextual retrieval layers, and vector-enabled data stores for Retrieval-Augmented Generation (RAG ...
Ottawa, ON · Hybrid
CA$106K - CA$118K/yr
Design data architectures that support AI-ready data access, including structured knowledge bases, contextual retrieval layers, and vector-enabled data stores for Retrieval-Augmented Generation (RAG ...
Toronto, ON · On-site
CA$70/hr
Knowledge or hands-on experience with Deep Learning architectures and Generative AI (e.g., LLMs, building Retrieval-Augmented Generation (RAG) pipelines). Retail Domain Expertise: Previous experience ...
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Toronto, ON · On-site
CA$70/hr
Knowledge or hands-on experience with Deep Learning architectures and Generative AI (e.g., LLMs, building Retrieval-Augmented Generation (RAG) pipelines). Retail Domain Expertise: Previous experience ...
Retrieval-Augmented Generation (RAG): Familiarity with building RAG architectures utilizing vector databases (like Amazon OpenSearch Serverless) to securely query unstructured healthcare ...
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Retrieval-Augmented Generation (RAG): Familiarity with building RAG architectures utilizing vector databases (like Amazon OpenSearch Serverless) to securely query unstructured healthcare ...
... Retrieval-Augmented Generation, Agentic AI frameworks, LLM orchestration, vector search, AI APIs, and Azure-based AI governance.Operating with a high degree of autonomy, the Lead Solution Architect ...
... Retrieval-Augmented Generation, Agentic AI frameworks, LLM orchestration, vector search, AI APIs, and Azure-based AI governance.Operating with a high degree of autonomy, the Lead Solution Architect ...
... Retrieval-Augmented Generation, Agentic AI frameworks, LLM orchestration, vector search, AI APIs, and Azure-based AI governance.Operating with a high degree of autonomy, the Lead Solution Architect ...
... Retrieval-Augmented Generation, Agentic AI frameworks, LLM orchestration, vector search, AI APIs, and Azure-based AI governance.Operating with a high degree of autonomy, the Lead Solution Architect ...
Hands-on expertise developing Retrieval-Augmented Generation (RAG) solutions, including embeddings, semantic search, knowledge grounding, context engineering, prompt optimization, and prompt ...
Hands-on expertise developing Retrieval-Augmented Generation (RAG) solutions, including embeddings, semantic search, knowledge grounding, context engineering, prompt optimization, and prompt ...
Hands-on expertise developing Retrieval-Augmented Generation (RAG) solutions, including embeddings, semantic search, knowledge grounding, context engineering, prompt optimization, and prompt ...
Hands-on expertise developing Retrieval-Augmented Generation (RAG) solutions, including embeddings, semantic search, knowledge grounding, context engineering, prompt optimization, and prompt ...
Ottawa, ON · On-site
... and retrieval-augmented generation (RAG) pipelines * Contribute to prompt engineering and integration of LLMs into web-based or API-driven applications * Support data preprocessing, embedding, and ...
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Ottawa, ON · On-site
... and retrieval-augmented generation (RAG) pipelines * Contribute to prompt engineering and integration of LLMs into web-based or API-driven applications * Support data preprocessing, embedding, and ...
Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base workflows. * Hands-on experience with LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, or other related AI ...
New
Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base workflows. * Hands-on experience with LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, or other related AI ...
New
Work hands-on with agent frameworks, retrieval-augmented generation pipelines, and LLM-powered systems in production. - Entrepreneurial team:We move fast, experiment often, and ship real products.
Work hands-on with agent frameworks, retrieval-augmented generation pipelines, and LLM-powered systems in production. - Entrepreneurial team:We move fast, experiment often, and ship real products.
Design and implement advanced generative AI methods, including sophisticated prompt engineering and Retrieval-Augmented Generation (RAG) . * Build and optimize RAG systems , including hybrid search ...
Design and implement advanced generative AI methods, including sophisticated prompt engineering and Retrieval-Augmented Generation (RAG) . * Build and optimize RAG systems , including hybrid search ...
Toronto, ON · On-site
Build Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, embeddings, vector search, and re-ranking * Build clean, well-tested RESTful and/or gRPC APIs ...
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Toronto, ON · On-site
Build Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, embeddings, vector search, and re-ranking * Build clean, well-tested RESTful and/or gRPC APIs ...
Work hands-on with agent frameworks, retrieval-augmented generation pipelines, and LLM-powered systems in production. - Entrepreneurial team:We move fast, experiment often, and ship real products.
Work hands-on with agent frameworks, retrieval-augmented generation pipelines, and LLM-powered systems in production. - Entrepreneurial team:We move fast, experiment often, and ship real products.
Architect and optimize Retrieval-Augmented Generation (RAG) pipelines, semantic and hybrid search workflows, and context-assembly engines to deliver accurate, high-relevance information to downstream ...
Architect and optimize Retrieval-Augmented Generation (RAG) pipelines, semantic and hybrid search workflows, and context-assembly engines to deliver accurate, high-relevance information to downstream ...
Toronto, ON · Hybrid
CA$100K - CA$145K/yr
Design and implement advanced AI systems, including multi-component pipelines, Retrieval-Augmented Generation (RAG) architectures, and custom AI agents Ensure system quality, reliability, and ...
Toronto, ON · Hybrid
CA$100K - CA$145K/yr
Design and implement advanced AI systems, including multi-component pipelines, Retrieval-Augmented Generation (RAG) architectures, and custom AI agents Ensure system quality, reliability, and ...
A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.
A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.
To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.
For Retrieval Augmented Generation jobs in Ontario, the most frequently searched job titles are:
The top searched job categories for Retrieval Augmented Generation jobs in Ontario are:
Cities in Ontario with the most Retrieval Augmented Generation job openings:
Ottawa, ON • On-site
CA$239.47/hr
Part-time
PTO
Re-posted 25 days ago
Posting Reason:
New PositionLocation:
Main CampusAcademic Period:
2026 Fall SemesterFaculty:
Faculte de genie / Faculty of EngineeringAcademic Unit:
Ecole de conception et d'innovation pedagogique en genie \\ School of Engineering Design and Teaching InnovationCourse Title:
Generative AI and Large Language ModelsCourse Code:
MIA5150Section:
BCourse Description:
Foundations and practices of Generative AI and Large Language Models (LLMs), covering the full lifecycle from model development to deployment. Explore generative model families, including Transformers, autoregressive models, diffusion models, GANs, and VAEs, and their multimodal applications across text, image, audio, and video. Modern techniques such as fine-tuning, parameter-efficient training, in-context learning, contrastive learning, retrieval-augmented generation (RAG), and multi-agent systems for enabling complex reasoning, coordination, and autonomous task execution are discussed. Key practices in prompt engineering, inference optimization, safety and alignment, and responsible AI deployment. Practical applications across diverse domains.Posting limited to:
Professeur a temps-partiel regulier / Regular Part-Time ProfessorDate Posted (YYYY/MM/DD):
2026/05/26Applications must be received BEFORE (YYYY/MM/DD):
2026/08/23Expected Enrolment:
30Approval date:
2026/07/22Number of credits:
3Work Hours:
39Hourly Rate:
Enseignement / Teaching: $239.47 (2024-2025)The academic year starts on September 1 and ends on August 31.
These rates do not included vacation pay nor statutory pay.
These rates will be applied until a new collective agreement is ratified. Retro will be paid after the ratification.
Course type:
BPosting type:
Regulier / RegularLanguage of instruction:
Anglais | EnglishCompetence in second language:
ActiveCourse Schedule:
Mardi | Tuesday 19:00-22:00 - -Requirements:
Additional Information and/or Comments:
The course is onlineAn acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience. If you are invited to continue the selection process, please notify us of any adaptive measures you might require. Information you send us will be handled respectfully and in complete confidence. Employees are required under provincial law to successfully complete all mandatory legislated training. The list of training may be modified by provincial law.
The hiring process will be governed by the current APTPUO collective agreements; you can click here for the main unit, here for the OLBI unit, or here for the Toronto/Windsor unit to find out more.
The University of Ottawa embraces diversity and inclusion in the workplace. We are passionate about our people and committed to employment equity. We foster a culture of respect, teamwork and inclusion, where collaboration, innovation, and creativity fuel our quest for research and teaching excellence. While all qualified persons are invited to apply, we welcome applications from qualified Indigenous persons, racialized persons, persons with disabilities, women and LGBTQIA2S+ persons. The University is committed to creating and maintaining an accessible, barrier-free work environment. The University is also committed to working with applicants with disabilities requesting accommodation during the recruitment, assessment and selection processes. Applicants with disabilities may contact vra.affairesprofessorales@uottawa.ca to communicate the accommodation need. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to be fully vaccinated against Covid-19 as defined in Policy 129 - Covid-19 Vaccination. This policy was suspended effective May 1, 2022 but may be reinstated at any point in the future depending on public health guidelines and the recommendations of experts.
