AI Scientist & Engineer, Assurance Innovation Lab
$110,000–$160,000 year
HybridToronto, Ontario, Canada or Vancouver, British Columbia, Canada
Job Summary
Design, build, and deploy production-grade agentic workflows, retrieval-augmented generation solutions, and custom large language models to modernize operational processes within the Assurance practice. Extract high-value insights from complex datasets, optimize machine learning models for reliability and explainability, and develop intelligent solutions leveraging NLP, knowledge graphs, and predictive analytics. Collaborate cross-functionally with transformation managers, data scientists, and engineering teams to prototype emerging AI technologies, validate concepts, and scale successful initiatives while adhering to enterprise governance frameworks.
Required Qualifications
- Expert-level Python
- Deep experience with OpenAI API, Anthropic, Hugging Face, LangChain, LlamaIndex, and LangGraph
- Comprehensive experience with PyTorch, TensorFlow, Scikit-Learn, Pandas, NumPy, and Matplotlib
- Practical knowledge of training and fine-tuning open-source LLMs/transformers (e.g., Llama, Mistral) and implementing Knowledge Graphs
- Hands-on experience with Pinecone, Milvus, Weaviate, and standard SQL/NoSQL databases
- Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps tracking platforms (MLflow, Weights & Biases)
- Strong working knowledge of enterprise cloud environments including Microsoft Azure (Azure AI / AI Foundry), AWS (Bedrock), or GCP
- Demonstrated mastery of Retrieval-Augmented Generation (RAG) architectures and multi-Agent AI design patterns
- 3–5 years of hands-on experience building, fine-tuning, deploying, and monitoring machine learning models and Generative AI solutions in an enterprise production environment
Desired Qualifications
- Professional proficiency in R, Scala, Java, or TypeScript
- Published academic research in top-tier ML/AI conferences/journals
- demonstrated practical excellence through Kaggle competitions
- Strong business curiosity and problem-solving mindset
- Passion for applying AI and data science to practical operational challenges
- Ability to balance experimentation with scalable execution
- Strong collaboration and stakeholder engagement skills
- Interest in workflow modernization, intelligent automation, and future-state operating models
- Passion for continuous learning and emerging technologies
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