> Markdown version of [/jobs/ext/4618426-software-engineer-river-api](https://www.wearedevelopers.com/jobs/ext/4618426-software-engineer-river-api). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Software Engineer, River API

- **Company:** River AI
- **Location:** Palo Alto, CA, United States
- **Salary:** $200,000.0
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Systems Engineering, C++ (Programming Language), Computer Engineering, Concurrent Computing, Extract Transform Load (ETL), Software Debugging, Distributed Systems, Memory Management, Fault Tolerance, InfiniBand, PCI Express, Remote Direct Memory Access, System Programming, Pytorch, Information Technology
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_116ed891e69ca8d836584382fc8899a8

## About the Role

* Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical industry experience.
 * Deep expertise in systems-level languages (C, C++, or Rust) with a track record of writing performant, maintainable code.
 * Strong foundation in computer architecture, memory management, and concurrent programming.
 * Exceptional debugging skills, especially when tackling complex, non-deterministic issues in distributed environments.
 * A highly collaborative mindset and a bias for action to push boundaries across the stack., * Hands-on experience with modern AI frameworks (e.g., PyTorch, JAX) and tooling for large-scale model training.
 * Deep familiarity with modern GPU architectures (NVIDIA/AMD) and hardware constraints (HBM bandwidth, PCIe limits).
 * A proven track record of shipping and maintaining high-performance distributed systems or low-level software libraries.

## Description

We are looking for exceptional systems engineers to build the high-performance engines that train our models. Your goal is to make training at River fast, reliable, and massively scalable.

You will take ownership of our core infrastructure stack; from writing custom GPU kernels to managing clusters of thousands of nodes, ensuring our researchers can focus on science rather than system bottlenecks.

What You'll Do

 * 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.