Senior Runtime Engineer for Scalable AI Systems

Cerebras; Raleigh (NC); On-site; USD 140,000 - 230,000; Full time

Job summary

Cerebras Systems is hiring for a role focused on building and optimizing distributed runtime software that orchestrates massive compute and data pipelines across heterogeneous clusters. You will push concurrency, throughput, and scalability for AI workloads at scale, collaborating with ML and compiler teams, and shaping end-to-end model execution from data ingestion to distributed execution.

Ideal candidates have strong C/C++ skills, experience with distributed systems, and a background in

Qualifications

• 3+ years of experience in high-performance or distributed system software.
• Strong C/C++ programming skills with multithreading, memory management and optimization.
• Experience with distributed systems, networking, or IPC.
• Solid understanding of data structures, concurrency, and system-level resource management.
• Ability to debug, profile and optimize code across scales—from threads to clusters.
• Bachelor’s, Master’s, or equivalent in CS/EE.

Responsibilities

• Design and implement distributed runtime components to efficiently manage large-scale execution workloads.
• Develop and optimize high-performance data and communication pipelines that fully utilize CPU, memory, storage, and network resources.
• Enable scalable execution across multiple compute nodes, ensuring high concurrency and minimal bottlenecks.
• Collaborate with ML and compiler teams to integrate new model architectures and hardware-specific optimizations.
• Diagnose and resolve complex performance issues across the software stack using profiling tools.
• Contribute to system design, architecture reviews, and roadmap planning for large-scale AI workloads.

Skills

C/C++ programming

Multithreading

Distributed systems

Profiling & debugging

Concurrency

Memory management

System resource management

Education

Bachelor’s or Master’s in CS/EE

Tools

Python

PyTorch

MPI/Distributed tooling

Job description

Cerebras Systems is hiring for a role focused on building and optimizing distributed runtime software that orchestrates massive compute and data pipelines across heterogeneous clusters. You will push concurrency, throughput, and scalability for AI workloads at scale, collaborating with ML and compiler teams, and shaping end-to-end model execution from data ingestion to distributed execution.

Ideal candidates have strong C/C++ skills, experience with distributed systems, and a background in