Senior AI Scientist

Location: Toronto, ON, Canada; hybrid arrangement with 1–3 days per week on-site at Toronto-81 Bay and the remaining days remote. Candidates must be legally eligible to work at the specified location and may need a valid work or study permit.

Company

hirify.global is a relationship-oriented bank whose Enterprise Advanced Analytics and Artificial Intelligence team develops and deploys practical AI, machine learning, and natural language processing solutions across the bank.

What you will do

• Design, build, and deploy practical AI solutions from early prototypes to scalable, production-ready capabilities.
• Develop end-to-end solutions using structured and unstructured data, taking them from experimentation through deployment and adoption.
• Build reusable tools, APIs, and accelerators for teams across the bank, using AI-assisted development tools such as GitHub Copilot.
• Partner with product, technology, marketing, channels, risk, and Capital Markets stakeholders to translate business needs and data into measurable insights and solutions.
• Improve machine learning techniques, engineer relevant features, and contribute to scalable data products.
• Partner with data scientists and engineers, mentor junior team members, and provide technical guidance.

Requirements

• Experience designing, building, and delivering end-to-end machine learning, NLP, and Generative AI solutions from proof of concept to production with measurable business value.
• Experience building LLM applications using prompt engineering, RAG, and agentic workflows, with frameworks such as LangChain, LangGraph, or Microsoft Agent Framework.
• Experience applying tool calling, memory, evaluation, and guardrails for secure and reliable use in regulated environments.
• Hands-on production experience with Python, SQL, Spark, APIs, automated testing, Git-based workflows, Azure, Databricks, Azure DevOps, and GitHub Actions.
• Strong knowledge of machine learning algorithms, statistical methods, and model evaluation techniques, including interpreting patterns, validating results, and measuring performance in a business context.
• Ability to build strong relationships, collaborate with diverse perspectives, and contribute to an inclusive team environment.
• High standards, genuine care in professional relationships, and motivation to grow with a values-oriented employer.
• Legal eligibility to work at the specified location and, where applicable, a valid work or study permit.

Nice to have

• Experience with Docker, Kubernetes, and MLOps/LLMOps practices, particularly in financial services or other highly regulated sectors.

Culture & Benefits

• Full-time regular employment with a 37.5-hour work week and a hybrid work arrangement.
• Competitive salary, incentive pay, banking benefits, a benefits program, and a defined benefit pension plan, subject to plan terms and conditions.
• Employee share purchase plan, vacation offering, wellbeing support, and a points-based recognition program.
• Professional growth and development opportunities, including a paid Purpose Day.
• Inclusive and accessible candidate and workplace environment.

Hiring process

• An attribute-based assessment and other skills tests may be required, including simulation, coding, or French proficiency assessments.
• Artificial intelligence tools are used during the recruitment process.