AI Scientist & Engineer, ASR

Putting people first, every day

BDO is a firm built on a foundation of positive relationships with our people and our clients. Each day, our professionals provide exceptional service, helping clients with advice and insight they can trust. In turn, we offer an award-winning environment that fosters a with a high priority on your personal and professional growth.

Your Opportunity

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. You will be working with our high-performing innovation team, dedicated SMEs from our assurance practice and highly skilled professionals from our AI Studio, nationwide.

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 net new 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.

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 tailored to business needs.

• 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

How do we define success for your role?

• You demonstrate BDO's core values through all aspect of your work: Integrity, Respect and Collaboration

• You understand your client’s industry, challenges, and opportunities; clients describe you as positive, professional, and delivering high-quality work

• You identify, recommend, and are focused on effective service delivery to your clients

• You share in an inclusive and engaging work environment that develops, retains & attracts talent

• You actively participate in the adoption of digital tools and strategies to drive an innovative workplace

• You grow your expertise through learning and professional development.

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.