Design Verification Emulation
River AI
Design Verification Emulation
River AI
API for fine-tuning open-weight models
At River AI, our mission is to create personal AI owned and shaped by each individual. To achieve this, we are rewriting the entire stack from scratch: personal hardware for local inference, bespoke training infrastructure, next-generation UIs, and frontier deep learning research.
We are scientists, engineers, and builders from the industry's top tech companies and AI labs. We bring a proven track record of scaling consumer systems for hundreds of millions of users and architecting the pre-training infrastructure behind today's frontier models.
We are seeking an emulation-focused design verification engineer to drive IP and SoC verification on emulation platforms. Working with simulation-based DV teams, you will translate architectural and microarchitectural definitions into workloads suited to emulation, then adapt and run those tests. You will partner with DV block owners on debug and emulation-specific closure, providing emulation signoff as an input to overall verification signoff. You will also develop the models and infrastructure needed to support this work.
Minimum Qualifications:
Preferred Qualifications: (We encourage you to apply even if you don’t meet all of these)
Logistics & Benefits
River AI helps developers and enterprises train, fine-tune, and own custom open-weight AI models using its River API, which focuses on open-weight models rather than a single lab-owned general model. The API supports LoRA fine-tuning and reinforcement learning on frontier open weights, featuring fast weight transfers, sampling-training consistency, elastic compute, and token-based billing that avoids idle GPU charges. It differentiates itself by enabling true ownership and control of models, offering a full-stack solution for training, fine-tuning, and deploying custom models without relying on a centralized general model. Its goal is to empower individuals and organizations to own, customize, and run their own AI systems with close-to-the-user control.
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