Hire for vLLM Mastery
vLLM is a specialized engine for one of the hardest problems in generative AI: **fast, cost-effective LLM inference**. Standard serving solutions are notoriously inefficient, but you need an engineer who can solve this bottleneck. Our vetting identifies experts in low-level LLM optimization who use vLLM’s core innovation, PagedAttention, to maximize GPU utilization. They don’t just deploy models; they build highly-tuned serving engines that deliver higher throughput at a fraction of the cost.
Sound Familiar?
Common problems we solve by providing true vLLM experts.
Prohibitively High Cost of LLM Inference
The Problem
Your LLM application is bleeding money. The cost of the GPU servers required to handle your user load is unsustainable, and your cost-per-token makes the entire business model ROI-negative.
The TeamStation AI Solution
A vLLM expert uses PagedAttention to dramatically improve GPU memory efficiency, allowing you to serve more concurrent users on a single GPU. This directly translates to a massive reduction in your hardware footprint and operational costs.
Proof: Increase inference throughput by up to 24x, delivering a >90% reduction in cost-per-token.
Slow, Unresponsive User Experience
The Problem
Your generative AI application is too slow for real-time interaction. High latency between a user’s prompt and the model’s response creates a frustrating, laggy experience that drives users away.
The TeamStation AI Solution
Our vLLM specialists optimize your serving stack for low latency. By implementing continuous batching and other advanced techniques available in vLLM, they ensure that the model generates responses as quickly as possible, enabling truly interactive applications.
Proof: Reduce time-to-first-token latency by 50% or more.
Wasted, Underutilized GPU Resources
The Problem
Your expensive GPU fleet is sitting idle most of the time. Standard batching methods are inefficient, leaving valuable compute resources unused while user requests queue up, creating a vicious cycle of high cost and poor performance.
The TeamStation AI Solution
A TeamStation vLLM engineer implements continuous batching to ensure your GPUs are always working at maximum capacity. This eliminates idle time and maximizes the value of your hardware investment, allowing you to serve peak traffic without over-provisioning.
Proof: Improve effective GPU utilization from <30% to over 80%.