Mirendil

Member of Technical Staff, Inference

San Francisco · Staff+

Sponsorship not specified$300k-$500kDetected 28 days ago

LLMsResearch

About the role

You'll work across the full inference stack, from serving infrastructure down to hardware-level optimization.
Some example areas you might work on (not limited to):
If you're excited about pushing the performance limits of frontier model inference, we'd love to hear from you.

Design and build high-throughput, low-latency inference serving systems for frontier models, optimizing for both research iteration and production deployment
Implement and validate inference-time optimizations: speculative decoding, quantization, KV cache management, and batching strategies
Build observability and reliability infrastructure so the team can measure latency, throughput, and cost across every serving configuration
Partner directly with teams to bring new model architectures and post-training techniques into production quickly

We offer a base salary of $300,000–$500,000 USD and a meaningful equity grant, depending on experience and background, along with competitive benefits.

We offer a base salary of $300,000-$500,000 USD and a meaningful equity grant, depending on experience and background, along with competitive benefits.
Our work spans areas such as model training, reinforcement learning, reasoning systems, and infrastructure for large-scale experiments.

We are building a frontier AI research company and training our own models end-to-end.
We are looking for an engineer to own the inference systems that power our models in production and research.

This listing is sourced directly from Mirendil's careers page and normalized into a canonical job model.