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AI Systems Design & Inference Engineering — Enrollment
by Abi Aryan ☯︎ · Education & Coaching
Summary
Unlock practical, production-ready skills to design scalable AI inference systems, optimize GPU memory usage, and reduce latency across real-world workloads. Gain actionable patterns, case-based guidance, and benchmarks that speed up deployment and improve reliability compared to ad-hoc approaches.
Primary Outcome
Master scalable AI inference design to deliver reliable, low-latency performance while optimizing memory and resource usage in production environments.
Who This Is For
- Senior AI engineers deploying production inference pipelines at scale
- Platform/SRE engineers responsible for GPU memory management and latency optimization
- Engineering managers seeking to upskill teams in AI systems design and deployment
What You'll Learn
- Hands-on curriculum covering GPU memory management
- Practical inference design patterns for production
- Real-world case studies from high-load AI apps
- Benchmark-driven optimization methods
Metadata
- Category
- Education & Coaching
- Creator
- Abi Aryan ☯︎
- Creator Title
- ML Research Engineer | Author: LLMOps & GPU Engineering | Making AI Systems go brrrr...
- Tags
- AI Strategy, AI Tools, Product Analytics, Automation
- Published
- 2026-02-16
- Last Updated
- 2026-02-25
Citation
"AI Systems Design & Inference Engineering — Enrollment" by Abi Aryan ☯︎, PlaybookHub — https://playbooks.rohansingh.io/playbook/ai-systems-design-inference-engineering-enrollment