ML Performance Benchmarking Engineer
Core
Design and implement end-to-end telemetry systems, build automation for performance data analysis, and analyze system behavior to optimize AI inference on the Cerebras Wafer-Scale Engine.
Role type
ML Performance Benchmarking Engineer
Builds
Telemetry systems, benchmarking infrastructure, and performance analysis tools for the Cerebras Wafer-Scale Engine (WSE)
Domain
AI hardware inference systems and large-scale computing infrastructure
Deliverable
production ML models
Required skills
Python, C++, automated infrastructure scaling, throughput optimization, complex system analysis, problem-solving, analytical mindset
Preferred skills
hardware-software intersection expertise, AI workload and architecture experience
Technologies
Python, C++, Cerebras Wafer-Scale Engine (WSE)
Responsibilities
Design and implement end-to-end telemetry systems across the software stack; Architect, build, and scale automation for generating and visualizing performance data; Dissect performance bottlenecks to deliver actionable insights; Partner with Core Platform teams to define testing methodologies for inference features
Seniority
Mid-level, hands-on IC
