AI Scientist & Engineer, ASR
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Key skills for this role
About the Role
BDO Canada is seeking an AI Scientist & Engineer to bridge data science and enterprise software engineering in the Assurance Innovation Lab. You will build custom LLMs, RAG solutions, and agentic workflows, working with cross-functional teams.
Key Skills for This Role
Responsibilities
- Collect, clean, and transform large, complex datasets for analysis
- Build custom machine learning models and NLP systems using state of the art techniques
- Leverage tools like TensorFlow, PyTorch, Kubernetes, and Nvidia Triton Servers to develop specialized LLMs
- Train, evaluate, and optimize models for accuracy, explainability, and ethical alignment
- Communicate technical analysis and results to stakeholders using data visualizations, reports, and presentations
- Continuously monitor models and data pipelines in production to ensure quality and reliability
- Stay up to date on the latest advancements in deep learning, NLP, reinforcement learning, and other AI methods
- Understand the Assurance practice end to end and the needs of Assurance practitioners
Requirements
- 3 5 years of hands on experience building, fine tuning, deploying, and monitoring ML models and Generative AI solutions in enterprise production
- Expert level Python proficiency
- 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)
- Hands on experience with vector databases (Pinecone, Milvus, Weaviate) and SQL/NoSQL databases
- Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps platforms (MLflow, Weights & Biases)
- Strong working knowledge of enterprise cloud environments (Azure AI, AWS Bedrock, or GCP)
- Demonstrated mastery of RAG architectures and multi agent AI design patterns
Full Job Posting
Your Opportunity
- We are looking for an AI Scientist & Engineer to bridge data science, experimental ML, and scalable enterprise software engineering in the Assurance Innovation Lab.
- This hybrid role involves extracting insights from complex datasets, training custom LLMs, and building production grade agentic workflows and RAG solutions under enterprise governance frameworks.
Responsibilities
- Collect, clean, and transform large, complex datasets for analysis.
- Build custom machine learning models and natural language processing systems using state of the art techniques.
- Leverage tools like TensorFlow, PyTorch, Kubernetes, and Nvidia Triton Servers to develop specialized large language models.
- Train, evaluate, and optimize models for accuracy, explain ability, and ethical alignment.
- Clearly communicate technical analysis and results to stakeholders using data visualizations, reports, and presentations.
- Continuously monitor models and data pipelines in production to ensure quality and reliability.
- Stay up to date on the latest advancements in deep learning, NLP, reinforcement learning, and other AI methods.
- Understand our Assurance practice end to end, and the current and future needs of our Assurance practitioners.
Technical 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.
Compensation
- The expected range of compensation for this role is $98,000 to $128,000 annually.
Why BDO?
- BDO is a firm built on a foundation of positive relationships with our people and our clients.
- Our people first approach has earned us a spot among Canada’s Top 100 Employers for 2026.
- We offer a comprehensive total rewards program, flexible time off, and wellness initiatives.
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