R

River AI

API for fine-tuning open-weight models

Applied Researcher

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

About the Job

Requirements

  • A BS, MS, or Ph.D. in Computer Science, Machine Learning, Mathematics, or equivalent practical industry experience.
  • A strong understanding of modern deep learning architectures and practical experience training, fine-tuning, and evaluating language or multimodal models.
  • Extensive hands-on experience with PyTorch or JAX and a track record of writing clean, scalable code for model training and experimentation.
  • The ability to turn open-ended problems and imperfect real-world data into working models, using rigorous experiments and evaluation to guide decisions.
  • The ability to work directly with customers, learn new domains, and explain technical tradeoffs to technical and non-technical audiences.
  • A collaborative mindset, ownership of outcomes, and a bias for action in a fast-paced environment.

Responsibilities

  • Partner directly with customers across industries to understand their workflows, identify high-value modeling problems, and define success criteria.
  • Develop data preparation and curation pipelines with customer teams, turning domain-specific data and expert feedback into training datasets and representative evaluations.
  • Design and run training experiments using continued pre-training, supervised fine-tuning, reinforcement learning, and parameter-efficient fine-tuning (PEFT), selecting approaches that fit each customer's goals, data, and compute budget.
  • Build evaluation suites, analyze model failures, and iterate on data and training methods to improve quality, reliability, and performance on real customer tasks.
  • Work with customer engineers and River's infrastructure team to scale training runs, resolve bottlenecks, and support deployment and ongoing model improvement.
  • Turn lessons from customer engagements into reusable training recipes, evaluation tools, and improvements to River's platform.

Desired Qualifications

  • Experience delivering models for customer or industry use cases, with measurable improvements in model performance or business outcomes.
  • Expertise in reinforcement learning, preference optimization, synthetic data generation, or adapting models to specialized domains.
  • Experience with distributed training, experiment management, or deploying and monitoring models in production.
  • Experience partnering with domain experts and working with proprietary or sensitive datasets under customer privacy and security requirements.

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

Recently Posted Jobs

Explore more opportunities at River AI

See more jobs