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 performanceRequirements:
- 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 practicesTransform how teams leverage AI by refining infrastructure standards and enhancing model deployment processes.#J-18808-Ljbffr

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