AI Scientist & Engineer, Assurance Innovation Lab

BDO•Vancouver, BC

2d•CA$110,000 - CA$160,000•Hybrid

About The Position

We are looking for an exceptionally skilled, hands-on, and innovation-minded AI Scientist & Engineer to bridge the gap between advanced data science, experimental machine learning, and scalable enterprise software engineering in our new Assurance Innovation Lab. The Assurance Innovation Lab (ASR Labs) serves as the experimentation, innovation, and solution development engine supporting our practice. Working alongside other functions nationally - including our Innovation Operations, AI Studio – Central Lab, Central Data Team, and Innovation & Change (I&C) — you will help ideate, design, prototype, develop, and deliver scalable solutions that modernize how work gets done across our Assurance practice. In this net new role, you will work with a team dedicated to building modern applications, intelligent workflow solutions, integrations, and AI-enabled platforms that support business transformation and operational modernization initiatives across our practice. You will be reporting to our Head of ASR Transformation, and have a dotted line to our technically astute managers in our AI Studio – Central Lab. This hybrid role is responsible for extracting high-value insights from complex datasets, training custom large language models (LLMs), and designing, building, and deploying production-grade agentic workflows and retrieval-augmented generation (RAG) solutions. Operating under enterprise governance frameworks like ISO/IEC 42001 and the NIST AI Risk Management Framework (AI RMF), you will deliver responsible, scalable, and highly impactful AI systems that drive true business transformation. The ideal candidate for this role will have 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. This role rests on the ability to work cross-functionally with AI Architects, AI Studio Leads, ML Engineers, Data Scientists, Full Stack Developers, and citizen developers on firm-wide strategic initiatives.

Requirements

Expert-level Python is required.
Professional proficiency in R, Scala, Java, or TypeScript is highly desirable
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

Nice To Haves

A systematic approach to problem-solving and devising practical solutions for complex enterprise bottlenecks
Published academic research in top-tier ML/AI conferences/journals OR demonstrated practical excellence through Kaggle competitions
High passion for translating complex data and multi-agent system capabilities into tangible, actionable business value
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

Responsibilities

Design, build, train, and optimize machine learning and AI models to support Assurance transformation initiatives
Develop intelligent solutions leveraging NLP, generative AI, knowledge graphs, predictive analytics, and automation capabilities
Support experimentation and prototyping of emerging AI technologies and use cases within Assurance
Evaluate model performance, explainability, reliability, and responsible AI considerations
Contribute to development of scalable AI-enabled workflows and intelligent operational solutions
Partner closely with Transformation Relationship Managers (TRMs), Assurance practitioners, Innovation & Change (I&C), Data & Analytics, and leadership teams
Contribute to multidisciplinary teams focused on solving business problems through technology, AI, automation, and workflow redesign
Support rapid experimentation, prototyping, and scaling of innovative solutions within the Assurance R&D Lab
Help bridge strategy, business operations, and technical execution to accelerate transformation outcomes
Translate complex business problems into practical analytical and AI-driven solutions
Participate in discovery sessions, design thinking workshops, ideation activities, and working groups
Collect, clean, transform, and analyze large and complex datasets from multiple sources
Build and maintain scalable data pipelines and model integration frameworks
Support connected data and intelligence capabilities aligned to the broader Total Assurance Ecosystem strategy
Work with cloud-based environments and modern AI infrastructure to support scalable deployment and operationalization
Collaborate with engineering teams to productionize and operationalize solutions
Work closely with the Assurance R&D Lab to validate concepts, prototype solutions, and scale successful initiatives
Stay informed on emerging trends across AI, automation, Assurance technology, data science, and intelligent systems
Help evaluate external tools, platforms, and ecosystem opportunities relevant to Assurance Transformation
Contribute to a culture of experimentation, innovation, and continuous improvement