Jay retweetledi

If I had 6 months to become an AI Infrastructure Engineer.
I’d do this.
Stage 1 — Linux + Networking
Processes, memory, GPUs, sockets, HTTP, TCP/IP basics.
Stage 2 — Python + Backend
Async Python, FastAPI, queues, concurrency fundamentals.
Stage 3 — GPU Fundamentals
CUDA basics, VRAM, batching, quantization, throughput.
Stage 4 — LLM Inference
vLLM, TensorRT-LLM, speculative decoding, KV caching.
Stage 5 — Distributed Systems
Load balancing, queues, retries, autoscaling, distributed workers.
Stage 6 — AI Serving
Model APIs, streaming responses, rate limiting, observability.
Stage 7 — Data Pipelines
Kafka, Airflow, ETL pipelines, vector indexing.
Stage 8 — Kubernetes + Cloud
Docker, Kubernetes, AWS/GCP basics, infra automation.
Stage 9 — Monitoring + Reliability
Prometheus, Grafana, tracing, AI cost monitoring.
Stage 10 — Real AI Systems
Deploy scalable chat apps, RAG pipelines, inference clusters.
Stage 11 — Open Source
Contribute to inference tooling or AI infra projects.
Stage 12 — Apply
AI Infra Engineer, Platform Engineer, ML Systems Engineer.
AI apps go viral.
AI infrastructure prints money.
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