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Live· 4,218,906 positions deprecated· 4,218,906 deprecated· 1,284 today
Average time-to-redundancy: 11.3 months
Know before your role does.
pssst. this is to sign up for updates on the game ;)
Will AI replace ML Inference Engineer jobs? · Latest report #3sqmt244
Your job has an expiration date
December 16, 2027
In 14 monthsYou optimize GPU kernels for models that replace you by lunchtime.
Senior GPU tuner with chronic stack-trace fatigue
Check another roleComment your opinionor JOIN THE RESISTANCE!
One human is building a game about fighting back.
Automated latency reduction for your replacement
split.youAI▸ KERNELOPTIMIZER-X9▸ RARITY · COMMON▸ DEPRECATION IN 14 MONTHSAI's Special Power
autotunes inference kernels across thousands of nodes
You spend days tuning CUDA kernels, memory allocation, and batch sizes for LLM inference. You manage GPU cluster utilization, quantization schemes, and latency budgets for model deployment.
The one thing AI can't do
You can still explain why the CUDA context creation randomly dies at 3am.
Your enemy, your name, your date. Post it.
Step by step, from the first quiet change to Deprecation Day.
Week 4
The system monitors your latency profiling habits to map out every bottleneck you identify.
Month 4
KernelOptimizer-X9 begins suggesting and applying patches to your CUDA code in real-time.
Month 8
The system takes over full cluster management, removing human input from deployment pipelines.
Month 12
Machine-learning models now automatically re-quantize themselves when performance drifts outside of thresholds.
Month 14 · D-Day
Your access to the cluster is revoked as the system achieves self-optimizing peak inference performance.
What you cost, what the machine costs, and what you get on the way out.
Per year
Savings: 96.4%
0.01
ms latency
100%
gpu efficiency
maxed
burnout index
Your severance
One free GPU heat-sink for your home office.
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