
Senior GenAI Specialist
- Mississauga, ON
- Permanent
- Temps-plein
- Design, develop, and implement GenAI solutions for various financial applications, including personalized recommendations, risk assessment, fraud detection, and automated reporting. Explore and experiment with advanced GenAI concepts like Agentic AI.
- Design and implement intelligent chatbots.
- Process and analyze large datasets of structured and unstructured financial data.
- Architect and implement efficient RAG pipelines, leveraging tools like LlamaIndex and LangChain.
- Develop and refine advanced prompting strategies for LLMs.
- Test, evaluate, and analyze the performance of LLM and other GenAI models.
- Collaborate closely with engineering teams to deploy and maintain GenAI models in production environments, including containerization, CI/CD pipelines, and cloud infrastructure management.
- Communicate effectively with business stakeholders.
- Stay up to date with the latest advancements in GenAI research and development, including areas like Agentic AI.
- Master's degree or PhD in Computer Science, Engineering, Statistics, or a related field.
- 5-8 years of experience in AI/ML development, with a proven track record of building and deploying sophisticated GenAI applications.
- Deep understanding of GenAI models and architectures, including transformers, LLMs (e.g., Llama, Gemini, GPT-4), GANs, and diffusion models. Familiarity with Agentic AI concepts.
- Extensive experience with prompt engineering, fine-tuning LLMs, and evaluating their performance.
- Expert-level Python programming skills and proficiency with relevant libraries (e.g., Transformers, LangChain, TensorFlow, PyTorch, Pandas, NumPy, Scikit-learn, Flask/Django, LlamaIndex).
- Experience with vector databases (e.g., Pinecone, Weaviate, Chroma, Faiss, PostgreSQL with vector extensions) and implementing RAG pipelines using tools like LlamaIndex and LangChain.
- Strong software engineering skills, including containerization (Docker, Kubernetes), CI/CD pipelines, and cloud infrastructure management (AWS, Azure, GCP).
- Strong analytical, problem-solving, and communication skills.
- Experience with MLOps principles and tools.
- Excellent collaboration skills.
- Experience with financial data and applications, particularly in areas like fraud detection, risk management, or personalized financial advice.
- Strong understanding of financial markets and instruments.
- Familiarity with chatbot development frameworks and best practices, including conversational AI design and natural language understanding (NLU).
- Experience leading or contributing to complex data science or AI/ML projects in a fast-paced environment.
- Publications or presentations at conferences related to AI/ML or GenAI.
- Experience with data visualization and reporting tools (e.g., Tableau, Power BI, matplotlib, seaborn).
- Experience with SQL and NoSQL databases.
- Programming Languages: Python (expert proficiency required), SQL
- Python Packages: Transformers, LangChain, LlamaIndex, TensorFlow, PyTorch, Pandas, NumPy, Scikit-learn, Flask/Django, and other relevant data science, machine learning, and web development libraries.
- Deep Learning Frameworks: TensorFlow, PyTorch
- LLMs: Llama, Gemini, GPT-4, and other advanced LLMs.
- Vector Databases: Pinecone, Weaviate, Chroma, Faiss, PostgreSQL with vector extensions (pgvector).
- Cloud Platforms: AWS, Azure, GCP
- MLOps Tools: MLflow, Kubeflow, or similar.
- Containerization: Docker, Kubernetes
- CI/CD Tools: GitHub Actions, Jenkins, or similar.
- Version Control: Git
- Data Visualization & Reporting: Tableau, Power BI, matplotlib, seaborn.
- Databases: SQL and NoSQL databases.