Staff Engineer (AI)

TL;DR

Staff Engineer (AI): Building and optimizing the ML Platform that powers hirify.global's ML-driven products with an accent on low-latency model inference, large-scale feature stores, and LLM orchestration. Focus on defining long-term infrastructure strategy, designing scalable distributed systems, and improving MLOps maturity.

Location: Toronto, Canada

Salary: CA$208,000 – CA$312,000

Company

hirify.global is a financial infrastructure platform for businesses, processing over $1.9 T in payments volume per year.

What you will do

• Lead end-to-end architecture and system design for large, complex projects across the ML Platform.
• Define technical direction for low-latency model inference, large-scale feature stores, and LLM/agent orchestration.
• Transform complex user needs into a long-term platform strategy and product roadmap.
• Collaborate cross-functionally with ML engineers, data scientists, and senior leadership to increase ML velocity.
• Drive cross-team initiatives to improve MLOps maturity and development velocity across the company.
• Mentor and grow other engineers, serving as a role model for designing and operating great software systems.

Requirements

• 10+ years of professional software development experience with a solid background in service-oriented architecture and large-scale distributed systems.
• Proven track record as a technical lead, with the ability to provide direction and lead multi-team initiatives.
• Direct experience working on production ML platform services.
• Strong communication skills to explain complex technical concepts to both technical and non-technical stakeholders.
• Ability to operate with a high level of autonomy in ambiguous environments.
• Hands-on experience using AI tools to accelerate development workflows.

Nice to have

• Experience building large-scale serving or data infrastructure (e.g., model registries, real-time feature computation).
• Familiarity with LLM frameworks, RAG, and agentic AI patterns.
• Experience with cloud services such as AWS, SageMaker, Bedrock, or Databricks.
• Experience training and shipping machine learning models to production to solve critical business problems.

Culture & Benefits

• Opportunity to work on a platform affecting a significant portion of the global GDP.
• High level of autonomy and empowerment to make decisions with large company-wide impact.
• Collaborative environment working with geographically distributed teams.
• Culture focused on technical excellence and continuous professional growth through mentorship.