Core Responsibilities

• Develop parallel mining algorithms and models that scale up to multiple GPUs and instances
• Identify performance hotspots and bounds with CUDA profiling tools
• Perform in-depth code analysis and parallel model optimization to exploit the potential of latest GPU architectures and maximize CPU/GPU utility

Requirements

Minimum Requirements

• Hands on experience with CUDA C++ parallel programming, including CPU/GPU integration for high-throughput systems
• Sound knowledge of different generations of CUDA architectures, compute capabilities, performance optimization techniques
• Solid knowledge of software design and programming techniques
• Basic understanding of algorithms and mathematics

Interview process

1. Application - Resume review and email exchange
2. 1st round interview - Technical review
3. Work sample (optional)
4. 2nd round interview - Technical background interview with corporate partners