Join us at the intersection of machine learning, software, and reconfigurable hardware.
Career at Elastix
We’re building the infrastructure that powers the next generation of AI. If you’re driven by deep systems engineering, cutting-edge ML, and long-term impact, this is where your work shapes the future of inference.
Think creatively, challenge assumptions, and take smart risks through rapid and targeted exploration.
Prioritize outcomes that matter for customers, the business, and our long-term vision.
Stay adaptable, move with urgency, and learn as we go.
Work transparently, trust deeply, and collaborate with intention.
Open positions
Explore current roles across machine learning, systems software, hardware, and the teams supporting our work.
Model quality used to be AI’s limiting factor. Now, it’s model economics. Where cost per token, watts per rack, and tokens per second dominate the conversation, no topic is more pertinent than model optimizations. And, in that conversation, few optimizations are as well-known, and as misunderstood, as quantization.
In early 2026, Microsoft disclosed an $80 billion unfulfilled Azure order backlog due to insufficient electricity to power the deployments. CEO Satya Nadella confirmed on the record that their GPUs are sitting idle in inventory, waiting for installations that can’t proceed until the grid can deliver the load.
What if we could generate 100x more tokens for the same budget? What new possibilities and world-changing applications would open up if the cost of AI stopped being the deciding factor?
When most people think of Large Language Models (LLMs), they think of chatbots. However, this perspective drastically understates the true scope and technical necessity of the inference market. Inference is much more than typing a prompt and receiving a response. In reality, it’s become a basic compute primitive that powers the entire AI lifecycle.
Research, product updates, and a closer look at efficient AI inference.