Step into the role of Lead Engineer focusing on building AI model infrastructure. Harness GPU resources and create self-service platforms to enhance AI deployment capabilities.
As a Lead Engineer, your responsibilities include designing and operating GPU infrastructures tailored for diverse AI model use cases. You'll prioritize robust systems for model serving, while also implementing multi-model routing strategies. By spearheading initiatives on model optimization and self-service platforms, you will enhance team efficiency in deploying AI solutions.
Key Responsibilities:
• Design and manage GPU infrastructures for AI models
• Optimize model serving systems for latency and availability
• Drive comprehensive model lifecycle management




• Create self-service tools for developer teams
• Establish observability metrics for system performance
Requirements:
• 8+ years in software engineering
• Proven experience with ML infrastructure and cloud services
• Robust background in GPU-related technologies
• Proficient in Python, Go, or C++
• Familiarity with infrastructure-as-code practices
Transform how teams leverage AI by refining infrastructure standards and enhancing model deployment processes.
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📌 Lead Engineer for AI Model Infrastructure (Toronto)
🏢 Medium
📍 Toronto