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River AI

API for fine-tuning open-weight models

Software Engineer - River API

Applied Machine LearningConfirmed live in the last 24 hours
Full-timePalo Alto, CA, USAIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Computer Engineering, or equivalent practical industry experience.
  • Deep expertise in systems-level languages such as C, C++, or Rust, with a track record of writing performant, maintainable code.
  • A strong foundation in computer architecture, memory management, and concurrent programming.
  • Exceptional debugging skills, especially for complex, non-deterministic issues in distributed environments.
  • Hands-on experience with modern AI frameworks such as PyTorch or JAX and tooling for large-scale model training is preferred.
  • Deep familiarity with modern GPU architectures, including NVIDIA or AMD, and hardware constraints such as HBM bandwidth and PCIe limits is preferred.
  • A proven track record of shipping and maintaining high-performance distributed systems or low-level software libraries is preferred.

Responsibilities

  • Architect and deploy fault-tolerant distributed systems for training and inference workloads across clusters with thousands of nodes.
  • Design high-performance kernels to maximize tensor operation efficiency, memory throughput, and networking over InfiniBand/RDMA.
  • Profile systems end-to-end to resolve blockers across hardware, software, data-loading pipelines, and collective communication primitives.
  • Partner directly with research scientists to rapidly implement, optimize, and scale experimental model architectures.

Desired Qualifications

  • Hands-on experience with modern AI frameworks such as PyTorch or JAX and tooling for large-scale model training.
  • Deep familiarity with modern GPU architectures, including NVIDIA or AMD, and hardware constraints such as HBM bandwidth and PCIe limits.
  • A proven track record of shipping and maintaining high-performance distributed systems or low-level software libraries.

About the Company

River AI

API for fine-tuning open-weight models

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.

Company size
11-50
Company stage
Early VC
Total funding
$1.1B
Headquarters
Palo Alto, CA
Founded
2026

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