Staff/Principal GPU Kernel Optimization Engineer

AMD; Hyderabad; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

AMD in Hyderabad is seeking an experienced GPU Kernel Optimization Engineer to push performance for AI workloads. You will optimize low-level GPU kernels in C++ across multi-GPU setups and contribute to distributed inference and training frameworks.

The role emphasizes profiling, parallel computing, and rigorous documentation to share best practices and ensure robust, scalable solutions.

Qualifications

• Over +15 years of architecting software in GPU/ML domains.
• Strong track record optimizing GPU kernels in modern C++.
• Hands-on experience with frameworks such as PyTorch, VLLM, CUTLASS and Kokkos.
• Scripting in Python and good software development practices.
• Experience with Agile processes and design patterns.

Responsibilities

• GPU Kernel Optimization: Develop and optimize low-level GPU kernels to accelerate inference and training of ML models.
• Multi-GPU and Multi-Node Optimization: Design strategies for distributed training across GPUs/nodes.
• Performance Profiling: Profile system performance and identify bottlenecks with profiling tools.
• Parallel Computing: Implement multi-threading and GPU synchronization for scalability.
• Benchmarking and Testing: Create benchmarks and ensure performance criteria are met.
• Documentation: Produce detailed docs on optimizations and guidelines.

Skills

GPU kernel optimization

C++17/20/23

PyTorch

VLLM

CUTLASS

Kokkos

CUDA

Python scripting

Agile processes

Multithreading

Parallel computing

Tools

Profiling tools

Job description

WHAT YOU DO AT AMD CHANGES EVERYTHING

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.

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 benefits at a glance.

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 here.

This posting is for an existing vacancy.