They are reducing the cost of building LLM. They are hiring a Founding Machine Learning engineer. Their model router comes out of NLP research and they raised $9M from the likes of General Catalyst (Stripe, Airbnb) and NEA (Databricks, Salesforce). All of their sales have been inbound—they haven’t had to reach out to large enterprise customers, they have reached out for their product.

About the role:

Building a good model-router is technically challenging. It requires training reward models from human feedback, developing more effective routing models, reducing model costs, and hosting models in a production-ready way. In this role you will:

• Work alongside the founders to develop model-routing technology and bring it into production, shaping the direction of the product.
• Lead a team of ML engineers who left companies like Google and Microsoft
• Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our deployed models.

You'll thrive in this role if you:

• Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference.
• Worked on model evaluation, coding in Pytorch, and using LLMs in production.
• Have a good intuition for when off-the-shelf solutions will work, and build tools to accelerate your own workflow quickly if they won’t. Stay scrappy to get the job done.
• Can figure out what the most important problems are, own those problems end-to-end, and are willing to pick up whatever knowledge you're missing to solve that problem.
• Have at least 3 years of professional ML engineering experience or equivalent.