Distributed Training Systems Engineer

River AI Inc.; Palo Alto (CA); On-site; USD 200,000 - 420,000; Full time

Benefits offered by this job

Health, dental, and vision insurance

Unlimited PTO

Relocation assistance

Job summary

River AI Inc. is seeking exceptional systems engineers to build the distributed training engines behind the River API, making fine-tuning and reinforcement learning fast, numerically correct, and reliable across large GPU clusters.

You will own training workload execution, including gradient computation, optimizer updates, rollout coordination, and checkpoint recovery. You will collaborate with researchers and inference engineers to bring new learning methods into production and improve how

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or equivalent practical industry experience.
• Hands-on experience building or substantially improving distributed model-training systems.
• Strong proficiency in Python and a modern deep-learning framework, such as PyTorch or JAX.
• Solid understanding of backpropagation, optimizers, mixed-precision training, and GPU memory management.
• Strong debugging skills across concurrent execution, collective communication, and distributed failure recovery.
• A highly collaborative mindset and a bias for action to push boundaries across the stack.

Responsibilities

• Build and optimize distributed training for large dense and mixture-of-experts models, including low-rank adapter training.
• Improve reinforcement-learning pipelines by coordinating sampling, reward computation, training updates, and weight transfer.
• Optimize GPU memory use, parallelism, and communication to increase training throughput.
• Implement reliable checkpointing, resumption, and worker recovery while preserving consistent training state.
• Validate losses, gradients, and optimizer behavior, and diagnose numerical or distributed execution failures.
• Partner with researchers to implement new algorithms and make them accessible through the River API.

Skills

Python

PyTorch

JAX

Distributed training

Debugging distributed systems

Education

Bachelor’s degree in Computer Science/Engineering

Tools

CUDA

C++

Rust

NCCL

Job description

River AI Inc. is seeking exceptional systems engineers to build the distributed training engines behind the River API, making fine-tuning and reinforcement learning fast, numerically correct, and reliable across large GPU clusters.

You will own training workload execution, including gradient computation, optimizer updates, rollout coordination, and checkpoint recovery. You will collaborate with researchers and inference engineers to bring new learning methods into production and improve how