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River AI

API for fine-tuning open-weight models

Product Engineer - Personal AI

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timePalo Alto, CA, USAIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, a related technical field, or equivalent practical industry experience.
  • A proven track record of building and launching meaningful production software, ideally in consumer products, large-scale systems, or high-growth startups.
  • Deep backend expertise with practical experience in Rust, Python, databases, APIs, distributed systems, and production architecture.
  • Strong frontend or mobile capability with modern technologies such as TypeScript, React, React Native, Swift, or Flutter.
  • Exceptional product judgment and the ability to reason backward from user needs, alongside a high degree of ownership to navigate ambiguity.

Responsibilities

  • Design, build, and launch polished, responsive user-facing product experiences across modern web and mobile stacks, partnering closely with design.
  • Architect high-performance backend services in Rust and Python, managing APIs, data systems, job queues, event pipelines, and distributed systems at scale.
  • Integrate large language models into real user workflows, managing tool use, memory, retrieval, structured outputs, latency optimization, and cost control.
  • Own the core infrastructure needed to run a high-scale consumer AI product, including deployment, monitoring, CI/CD, cloud infrastructure, and incident response.
  • Partner with research and infrastructure teams to take ambiguous ideas from prototype to production, translating new model capabilities into understandable and trustworthy product experiences.

Desired Qualifications

  • Hands-on experience with large language model systems, including APIs, agents, tool calling, prompt iteration, evaluation frameworks, and inference constraints.
  • Fluency with modern infrastructure and deployment platforms, including cloud environments, containers, Kubernetes, and Terraform or equivalent infrastructure as code.
  • AI-native product instincts and an understanding that large language model products require continuous evaluation, instrumentation, and close attention to real user behavior.
  • Experience with systems reliability, including metrics, logs, alerts, and performance tuning for high-scale consumer products.

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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