Senior Deep Learning Performance Architect

This is a fully remote position, open to applicants in California, +1 more state.

📋 Description

• Create cutting-edge architectures to advance the performance and efficiency of deep learning.

• Assess performance, cost, and power trade-offs by constructing analytical models, simulators, and testing frameworks.

• Comprehend and evaluate the interaction between hardware and software architectures regarding future algorithms, programming paradigms, and applications.

• Analyze PPA (performance, power, area) for hardware characteristics and system-level architectural decisions.

• Construct high-level simulators using C++/Python.

• Collaborate actively with software, product, and research teams to shape the future of deep learning hardware and software.

⛳️ Requirements

• MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent professional experience.

• Over 6 years of significant work experience in a relevant field.

• Robust expertise in GPU or Deep Learning ASIC architecture for distributed training and/or inference across multi-chip/multi-node systems.

• Familiarity with performance modeling, architectural simulation, profiling, and analysis.

• Strong grounding in machine learning and deep learning, including knowledge of contemporary transformer-based architectures and their performance at scale.

• Proficient programming skills in Python, C, and C++.

🏝️ Benefits

• Equity.

• Comprehensive benefits.