Distributed Systems Engineer: Ray Data & AI Pipelines

EngRadar; San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

EngRadar in San Francisco is seeking a data systems engineer to improve Ray Data performance and scale AI workloads across production pipelines. You will design fault-tolerant data loading for training workloads.

The role emphasizes distributed systems, data processing, and deep knowledge of database internals; experience with Python and batch inference is required to optimize large-scale AI workloads.

Qualifications

• 3–4 years of experience in building scalable and fault-tolerant distributed systems.
• Experience with data processing and database internals.
• Passion for large-scale AI performance.

Responsibilities

• Improve the performance of Ray Data and multi-modal batch inference.
• Scale AI workloads across data pipelines for production training.
• Build stable, fault-tolerant data loading solutions for production workloads.

Skills

Distributed Systems

Data Processing

Database Internals

Python

Scalable Systems

Fault Tolerance

Machine Learning

AI Workloads

Batch Inference

Data Pipelines

Job description

EngRadar in San Francisco is seeking a data systems engineer to improve Ray Data performance and scale AI workloads across production pipelines. You will design fault-tolerant data loading for training workloads.

The role emphasizes distributed systems, data processing, and deep knowledge of database internals; experience with Python and batch inference is required to optimize large-scale AI workloads.