Research Software Engineer — Scalable RL & Distributed Training

Reflection AI; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Top-tier compensation

Comprehensive health insurance

Fully paid parental leave

Paid time off

Daily meals provided

Job summary

A leading AI research company in San Francisco is seeking a strong software engineer to architect and optimize the core training infrastructure for advanced AI models. Responsibilities include designing large-scale training systems, implementing cutting-edge techniques, and diagnosing performance bottlenecks. Candidates should have deep experience in distributed training or data infrastructure, and a solid background in software engineering. The position offers competitive compensation, health and wellness benefits, and a collaborative work environment.

Qualifications

• Strong software engineering background with experience in distributed systems.
• Proven ability to implement advanced machine learning algorithms.
• Experience with GPU training infrastructure and large-scale data pipelines.

Responsibilities

• Design and optimize large-scale training loops and data pipelines.
• Implement state-of-the-art techniques ensuring numerical stability and efficiency.
• Build tooling for launching and monitoring complex experiments.
• Diagnose bottlenecks across the training stack.

Skills

Distributed Training & Inference

Data Infrastructure

Machine Learning Algorithms

High-performance Computing

Software Engineering

Tools

PyTorch

JAX

Ray

Kubernetes

Slurm

Job description

A leading AI research company in San Francisco is seeking a strong software engineer to architect and optimize the core training infrastructure for advanced AI models. Responsibilities include designing large-scale training systems, implementing cutting-edge techniques, and diagnosing performance bottlenecks. Candidates should have deep experience in distributed training or data infrastructure, and a solid background in software engineering. The position offers competitive compensation, health and wellness benefits, and a collaborative work environment.