Software Engineer, ML Inference Platform

About the role

Join a new team dedicated to building the infrastructure that connects AI model development to reliable production environments. You will focus on the practical implementation of systems that package, deploy, and monitor AI capabilities to ensure they operate safely and efficiently at scale.

Key facts

What you'll do

• Develop and refine processes for packaging, versioning, and rolling back model artifacts.
• Create deployment and release pathways for services backed by AI.
• Implement systems for staged rollouts, shadow-serving, and comparing new models against incumbents.
• Improve observability, debugging, and runtime performance for model-based systems.
• Automate evaluation frameworks to support evidence-based release decisions.
• Standardize shared tools to reduce manual coordination across AI teams.

Requirements

• Bachelor degree in Computer Science, Engineering, or equivalent practical experience.
• 2 to 6 years of professional software engineering experience with a history of shipping production infrastructure.
• Ability to write maintainable code and apply engineering fundamentals to solve complex debugging problems.
• Experience working in ambiguous, cross-functional environments with evolving requirements.
• Expertise in building for reproducibility, operability, and rollout safety.

Nice to have

• Experience with cloud infrastructure, containerization, managed ML platforms, or service orchestration.
• Background in model serving, experiment tracking, artifact management, or ML lifecycle tools.
• Familiarity with distributed systems, search or relevance systems, and internal enablement tooling.
• Experience with testing, benchmarking, or evaluation frameworks for release management.
• Exposure to applied AI, speech technology, conversational systems, or customer-facing workflows.

Skills & tools

• Software engineering fundamentals
• Production infrastructure and platform systems
• Runtime and serving systems
• Evaluation and quality systems
• Distributed systems and service platforms

Practical notes

• The salary range provided is for Ontario, Canada, and covers base salary only; it excludes equity, bonuses, and benefits.
• This is an implementation-focused role rather than a research or generic support position.