ML Runtime and Kernel Engineer - Core ML

Cerebras Systems builds AI-focused wafer-scale computing hardware and platforms. The Core ML team is seeking an engineer to bridge machine learning research and efficient execution on Cerebras systems by developing runtime components and high-performance kernels. The role involves implementing algorithms, diagnosing performance bottlenecks, and delivering robust, high-performance ML capabilities across frameworks, compilers, runtimes, and low-level kernels.

Responsibilities:

• Design and implement runtime components and high-performance kernels required by novel Core ML algorithms
• Translate research prototypes into efficient implementations for the Cerebras platform, including reference implementations and comparisons on GPUs where useful
• Profile and debug performance across the ML framework, compiler, runtime, communication, and kernel layers
• Optimize computation, memory movement, communication, and concurrency for large-scale training and low-latency inference
• Develop benchmarks, instrumentation, and automated tests that validate functionality, performance, and numerical correctness
• Collaborate closely with Core ML researchers and compiler, runtime, kernel, and inference engineers to evaluate design alternatives and deliver end-to-end capabilities
• Contribute to software architecture and roadmap decisions by identifying recurring limitations and high-leverage platform improvements