About the role
AI Scientist & Engineer
Location: Hybrid – Canada (Toronto preferred; Kitchener-Waterloo, Vancouver, Oakville, Ottawa, and other major Canadian office locations considered)
Employment Type: Full-Time, Permanent
Salary: $98,000 – $128,000 CAD
Key Responsibilities
Design, build, deploy, and optimize enterprise-grade Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG) solutions. Collect, clean, transform, and analyze large, complex datasets to generate actionable business insights. Develop, fine-tune, evaluate, and monitor custom Large Language Models (LLMs) and advanced machine learning models. Build scalable AI applications using PyTorch, TensorFlow, Scikit-Learn, LangChain, LlamaIndex, LangGraph, and related AI frameworks. Design and implement multi-agent AI workflows, autonomous AI systems, and intelligent orchestration frameworks. Fine-tune open-source transformer models including Llama, Mistral, and other leading foundation models. Develop AI solutions leveraging Knowledge Graphs, vector databases, and semantic search technologies. Deploy and manage production AI workloads using Docker, Kubernetes, NVIDIA Triton Inference Server, MLflow, and Weights & Biases. Build AI applications utilizing OpenAI APIs, Anthropic, Hugging Face, and enterprise cloud AI platforms including Azure AI, AWS Bedrock, and Google Cloud Platform (GCP). Design scalable data pipelines and integrate AI models with SQL, NoSQL, and enterprise data platforms. Monitor production AI systems to ensure performance, reliability, explainability, governance, and responsible AI compliance. Collaborate closely with AI Architects, Machine Learning Engineers, Data Scientists, Software Developers, Assurance professionals, and business stakeholders to deliver innovative AI solutions. Translate complex AI research and emerging technologies into practical, scalable business applications. Produce clear technical documentation, presentations, visualizations, and executive-ready insights for both technical and non-technical audiences. Stay at the forefront of advancements in Generative AI, Natural Language Processing (NLP), Deep Learning, Reinforcement Learning, Agentic AI, and enterprise AI architectures. Contribute to a collaborative AI Innovation Lab focused on accelerating enterprise AI adoption and transforming business processes.
Qualifications
3–5+ years of hands-on experience designing, building, deploying, and supporting enterprise AI and machine learning solutions. Expert-level Python programming with experience in AI, data science, and production software development. Experience with one or more additional languages such as R, Scala, Java, or TypeScript. Strong experience developing production AI applications using modern LLM frameworks and MLOps best practices. Demonstrated expertise in RAG architectures, vector databases (Pinecone, Milvus, Weaviate), and multi-agent AI design patterns. Experience working within cloud environments including Microsoft Azure, AWS, or Google Cloud Platform (GCP). Knowledge of responsible AI frameworks including ISO/IEC 42001 and the NIST AI Risk Management Framework is considered an asset. Experience within AI innovation teams, enterprise transformation initiatives, consulting environments, or published AI/ML research is considered an asset.
This opportunity is ideal for a hands-on AI builder who enjoys solving complex business problems using cutting-edge artificial intelligence, machine learning, LLMs, and scalable cloud-native technologies while helping shape the future of enterprise AI innovation. ,
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About the role
AI Scientist & Engineer
Location: Hybrid – Canada (Toronto preferred; Kitchener-Waterloo, Vancouver, Oakville, Ottawa, and other major Canadian office locations considered)
Employment Type: Full-Time, Permanent
Salary: $98,000 – $128,000 CAD
Key Responsibilities
Design, build, deploy, and optimize enterprise-grade Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG) solutions. Collect, clean, transform, and analyze large, complex datasets to generate actionable business insights. Develop, fine-tune, evaluate, and monitor custom Large Language Models (LLMs) and advanced machine learning models. Build scalable AI applications using PyTorch, TensorFlow, Scikit-Learn, LangChain, LlamaIndex, LangGraph, and related AI frameworks. Design and implement multi-agent AI workflows, autonomous AI systems, and intelligent orchestration frameworks. Fine-tune open-source transformer models including Llama, Mistral, and other leading foundation models. Develop AI solutions leveraging Knowledge Graphs, vector databases, and semantic search technologies. Deploy and manage production AI workloads using Docker, Kubernetes, NVIDIA Triton Inference Server, MLflow, and Weights & Biases. Build AI applications utilizing OpenAI APIs, Anthropic, Hugging Face, and enterprise cloud AI platforms including Azure AI, AWS Bedrock, and Google Cloud Platform (GCP). Design scalable data pipelines and integrate AI models with SQL, NoSQL, and enterprise data platforms. Monitor production AI systems to ensure performance, reliability, explainability, governance, and responsible AI compliance. Collaborate closely with AI Architects, Machine Learning Engineers, Data Scientists, Software Developers, Assurance professionals, and business stakeholders to deliver innovative AI solutions. Translate complex AI research and emerging technologies into practical, scalable business applications. Produce clear technical documentation, presentations, visualizations, and executive-ready insights for both technical and non-technical audiences. Stay at the forefront of advancements in Generative AI, Natural Language Processing (NLP), Deep Learning, Reinforcement Learning, Agentic AI, and enterprise AI architectures. Contribute to a collaborative AI Innovation Lab focused on accelerating enterprise AI adoption and transforming business processes.
Qualifications
3–5+ years of hands-on experience designing, building, deploying, and supporting enterprise AI and machine learning solutions. Expert-level Python programming with experience in AI, data science, and production software development. Experience with one or more additional languages such as R, Scala, Java, or TypeScript. Strong experience developing production AI applications using modern LLM frameworks and MLOps best practices. Demonstrated expertise in RAG architectures, vector databases (Pinecone, Milvus, Weaviate), and multi-agent AI design patterns. Experience working within cloud environments including Microsoft Azure, AWS, or Google Cloud Platform (GCP). Knowledge of responsible AI frameworks including ISO/IEC 42001 and the NIST AI Risk Management Framework is considered an asset. Experience within AI innovation teams, enterprise transformation initiatives, consulting environments, or published AI/ML research is considered an asset.
This opportunity is ideal for a hands-on AI builder who enjoys solving complex business problems using cutting-edge artificial intelligence, machine learning, LLMs, and scalable cloud-native technologies while helping shape the future of enterprise AI innovation. ,