ML Algorithms Performance Engineer, Core ML (Hybrid)

We Love AI Jobs; Sunnyvale, Northern (CA, KY); Hybrid; USD 180,000 - 220,000; Full time

Job summary

Cerebras Systems seeks an ML Algorithm Mapping and Performance Engineer to map algorithms to the Cerebras architecture and benchmark against baselines. You will build analytical models, run end-to-end profiling, and drive design directions for hardware and software co-design.

The role requires strong architecture and ML fundamentals, plus hands-on prototyping and benchmarking across training and inference workloads on Cerebras hardware and GPU baselines.

Qualifications

• Proven ability to build analytical performance models for ML training and inference.
• Experience with benchmarking, system simulation, and performance tuning.
• Strong understanding of computer architecture and parallel computing.

Responsibilities

• Build analytical and empirical performance models for state-of-the-art ML training and inference algorithms.
• Characterize asymptotic behavior and identify how algorithmic trade-offs change with model size, sequence length, batch size, parallelism, and hardware scale.
• Construct Pareto frontiers across model quality, latency, throughput, memory footprint, communication, and compute cost.
• Develop prototype implementations and benchmarks for Cerebras WSE and relevant GPU or software baselines.
• Analyze system behavior to identify kernel, compiler, runtime, communication, and algorithmic bottlenecks.
• Evaluate emerging techniques in areas such as parallel token generation, diffusion and speculative decoding, attention, sparsity, mixture-of-experts, low-precision computation, and distributed training.
• Partner with researchers and kernel, compiler, runtime, inference, and architecture teams to recommend high-value implementation and co-design directions.
• Develop tools and visualizations that make performance projections, measurements, and design trade-offs understandable across engineering and research teams.
• Clearly communicate conclusions, assumptions, limitations, and recommendations through technical reports, presentations, and design reviews.

Skills

Analytical performance modeling

Benchmarking and system simulation

Computer architecture

Parallel computing

Python

C++

PyTorch

CUDA

Education

Bachelor’s, Master’s, PhD, or equivalent experience in CS/CE

Tools

PyTorch

CUDA

Job description

Cerebras Systems seeks an ML Algorithm Mapping and Performance Engineer to map algorithms to the Cerebras architecture and benchmark against baselines. You will build analytical models, run end-to-end profiling, and drive design directions for hardware and software co-design.

The role requires strong architecture and ML fundamentals, plus hands-on prototyping and benchmarking across training and inference workloads on Cerebras hardware and GPU baselines.