AI Scientist & Engineer
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Key skills for this role
About the Role
BDO Canada seeks an AI Scientist & Engineer to bridge data science and enterprise software engineering in the Assurance Innovation Lab. You will design, build, and deploy production-grade AI solutions including LLMs, RAG, and agentic workflows.
Key Skills for This Role
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, Assurance practitioners, Innovation & Change, Data & Analytics, and leadership teams
- Collect, clean, transform, and analyze large and complex datasets from multiple sources
- Build and maintain scalable data pipelines and model integration frameworks
- Work with cloud based environments and modern AI infrastructure to support scalable deployment and operationalization
- Collaborate with engineering teams to productionize and operationalize solutions
Requirements
- 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
- 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
Full Job Posting
Role Overview
- 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.
Key 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, Assurance practitioners, Innovation & Change, Data & Analytics, and leadership teams
- Collect, clean, transform, and analyze large and complex datasets from multiple sources
- Build and maintain scalable data pipelines and model integration frameworks
- Work with cloud based environments and modern AI infrastructure to support scalable deployment and operationalization
- Collaborate with engineering teams to productionize and operationalize solutions
Requirements
- Programming Languages: Expert level Python is required. Professional proficiency in R, Scala, Java, or TypeScript is highly desirable
- AI & LLM Frameworks: Deep experience with OpenAI API, Anthropic, Hugging Face, LangChain, LlamaIndex, and LangGraph
- Data Science & Deep Learning: Comprehensive experience with PyTorch, TensorFlow, Scikit Learn, Pandas, NumPy, and Matplotlib
- Model Training: Practical knowledge of training and fine tuning open source LLMs/transformers (e.g., Llama, Mistral) and implementing Knowledge Graphs
- Data & Vector Infrastructure: Hands on experience with Pinecone, Milvus, Weaviate, and standard SQL/NoSQL databases
- DevOps / MLOps: Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps tracking platforms (MLflow, Weights & Biases)
- Cloud Platforms: Strong working knowledge of enterprise cloud environments including Microsoft Azure (Azure AI / AI Foundry), AWS (Bedrock), or GCP
- Architecture & Patterns: Demonstrated mastery of Retrieval Augmented Generation (RAG) architectures and multi Agent AI design patterns
Ideal Candidate Will Have
- 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
Why Join the Assurance Innovation Lab?
- This is an opportunity to help build the future of Assurance through modern platforms, intelligent workflows, and scalable AI enabled solutions.
- You will join a high performing team to work on high impact transformation initiatives that directly influence how the business operates and delivers value.
- The role offers exposure to enterprise transformation and innovation programs, AI enabled applications, modern cloud and engineering ecosystems, and cross functional collaboration.
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