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Morph (YC S23) Is Hiring Member of Technical Stuff

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Why This Matters

Morph's focus on optimizing inference infrastructure for large-scale models is crucial for advancing AI deployment efficiency, reducing costs, and improving reliability. Their work directly impacts how quickly and economically AI models can be served, benefiting both industry players and consumers by enabling more accessible and scalable AI applications.

Key Takeaways

The best candidates would be top 1% at multiple parts of the inference stack.

work on PD disaggregation research

Morph builds the inference infrastructure behind the fastest open models. Our stack spans kernels, model serving, routing, autoscaling, and capacity. We are hiring a performance engineer to make the entire system faster, cheaper, and more reliable.

What you’ll do

Find the gap between theoretical hardware performance and production performance

Trace latency and throughput regressions from the API layer down to individual kernels

Optimize batching, scheduling, routing, quantization, and distributed execution

Build benchmarks and observability that make bottlenecks obvious

Validate that every optimization preserves model quality and correctness

Stack-rank opportunities and ship the highest-impact fixes yourself

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