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GPU Kernel Optimization Engineer

Key Responsibilities

GPU Kernel Optimization: Develop and optimize low-level GPU kernels to accelerate inference and training of large machine learning models. Maximize computational efficiency and reduce execution time while ensuring model accuracy.
Multi-GPU and Multi-Node Optimization: Design and implement strategies for distributed model training and inference across multiple GPUs and nodes. Address data parallelism and model parallelism challenges to fully utilize available resources.
Performance Profiling: Profile and analyze system and application performance to identify bottlenecks and areas for improvement. Use profiling tools to understand and optimize hardware resource utilization.
Parallel Computing: Leverage parallel computing techniques to improve the scalability and performance of machine learning workloads. Implement multi-threading and GPU synchronization techniques.
Benchmarking and Testing: Develop benchmarks and testing procedures to assess the performance and stability of optimized models and frameworks. Ensure that the solutions meet or exceed the defined performance criteria.
Documentation: Create detailed documentation of optimizations, best practices, and implementation guidelines to facilitate knowledge sharing and maintainable code.

Required Qualifications

Over +15 years of architecting software:

Optimizing GPU kernels in C++17, C++20, and C++23.
Working with complex frameworks/libraries such as ( PyTorch, VLLM, CUTLASS, Kokkos, etc.)
Practical working knowledge of GPU/CPU architectures.
Scripting knowledge (ex. Python)
Knowledge of software development processes.
Good coding practices and design pattern identification, and implementation
Agile processes and procedures

Over +10 years of working with:

Optimization in assembly
Strong experience in low-level GPU kernel optimization.
Proficiency in CUDA and GPU programming.
Experience with distributed computing and multi-GPU environments.
Proficiency in performance profiling and optimization tools.
Excellent problem-solving skills and attention to detail.
Strong communication and teamwork skills.

#DC-GPU

#LI-NR1

Benefits offered are described: .

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants needs under the respective laws throughout all stages of the recruitment and selection process.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's Responsible AI Policy is available

This posting is for an existing vacancy.

Staff/Principal GPU Kernel Optimization Engineer