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.

📌 Lead Engineer For Ai Model Infrastructure Toronto
🏢 Medium
📍 Toronto