Engineering Manager, Inference Ml Runtime

Cerebras Systems

Sunnyvale, California, USA
On-site
Ml inference runtime and serving systems
High-throughput, low-latency inference pipelines
Multimodal model execution
Cerebras Systems is seeking an Engineering Manager for their Inference ML Runtime team in Sunnyvale, CA, or Toronto, ON. The role requires strong technical leadership in building and scaling AI inference systems, with a focus on machine learning and distributed systems

Job Summary

  • Lead a team responsible for designing and scaling the systems that enable seamless execution of state-of-the-art AI models on Cerebras hardware.
  • Own the architecture and evolution of the ML inference runtime and serving systems, guiding the design of high-throughput, low-latency inference pipelines.
  • Scale Cerebras’ inference platform to handle large volumes of concurrent requests at very fast speed and drive improvements in latency, throughput, and compute efficiency.

Matching Summary

Match Score: 85

Cerebras Systems is seeking an Engineering Manager for their Inference ML Runtime team in Sunnyvale, CA, or Toronto, ON. The role requires strong technical leadership in building and scaling AI inference systems, with a focus on machine learning and distributed systems.

Skills & Requirements

Must-have

  • ML inference runtime and serving systems
  • High-throughput, low-latency inference pipelines
  • Multimodal model execution
  • Scalable serving infrastructure
  • Python and C++ programming
  • Large-scale inference systems

Nice-to-have

  • LLM serving frameworks
  • PyTorch and deep learning frameworks
  • Distributed systems and HPC
  • ML runtime systems
  • Performance optimization for AI workloads

Key Requirements

  • 8+ years of experience in large-scale software engineering or ML/distributed systems
  • 2+ years of engineering management experience
  • Experience building and scaling large-scale inference systems
  • Experience with cloud infrastructures and scalable microservices

Work Rights

Not specified

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