2 Performance Tuning jobs in Hyderabad

WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ Senior Software Architect – GPU Kernel Optimization & Distributed AI Systems THE TEAM: Join AMD’s high-impact team at the heart of innovation in AI, ML, and high-performance computing (HPC). We’re a collaborative group of software architects and GPU engineers focused on pushing the boundaries of AI model performance across distributed, GPU-accelerated platforms. Our work drives the next generation of AMD’s AI software stack, enabling large-scale machine learning training and inference workloads in data centers and enterprise environments. THE ROLE: As a Senior Software Developer, you will develop both GPU kernel-level optimization and distributed software efforts for large-scale AI workloads. This is a technical leadership role with direct influence over critical software components in AMD’s AI stack. You’ll architect and implement optimized compute kernels, guide software teams through the full product lifecycle, and work closely with internal and external partners to deploy scalable, high-performance solutions. THE PERSON: We’re looking for a highly skilled, deep systems thinker who thrives in complex problem domains involving parallel computing, GPU architecture, and AI model execution. You are confident leading software architecture decisions and know how to translate business goals into robust, optimized software solutions. You’re just as comfortable writing performance-critical code as you are guiding agile development teams across product lifecycles. Ideal candidates have a strong balance of low-level programming, distributed systems knowledge, and leadership experience—paired with a passion for AI performance at scale. KEY RESPONSIBILITIES: GPU Kernel Optimization: Develop and optimize GPU kernels to accelerate inference and training of large machine learning models while ensuring numerical accuracy and runtime efficiency. Multi-GPU and Multi-Node Scaling: Architect and implement strategies for distributed training/inference across multi-GPU/multi-node environments using model/data parallelism techniques. Performance Profiling: Identify bottlenecks and performance limitations using profiling tools; propose and implement optimizations to improve hardware utilization. Parallel Computing: Design and implement multi-threaded and synchronized compute techniques for scalable execution on modern GPU architectures. Benchmarking & Testing: Build robust benchmarking and validation infrastructure to assess performance, reliability, and scalability of deployed software. Documentation & Best Practices: Produce technical documentation and share architectural patterns, code optimization tips, and reusable components. PREFERRED EXPERIENCE: Software Team Leadership Collaboration with customers and business units to define deliverables and roadmaps. Interfacing with executive leadership on program progress and strategic planning. Experience in production-level software deployment (e.g., upstreaming to open source, commercial rollouts). Software Architecture Deep experience with GPU kernel optimization in C++12/17/20. Working knowledge of frameworks such as PyTorch, vLLM, Cutlass, Kokkos. Practical expertise in CPU/GPU architecture and system-level performance tuning. Proficiency in Python scripting and infrastructure automation. Application of software design patterns and industry-standard engineering practices. GPU & Low-Level Optimization Hands-on experience with CUDA and low-level GPU programming. Kernel optimization in assembly and tight loops for latency-sensitive code. Proficiency with performance profiling tools (Nsight, VTune, Perf, etc.). Experience with distributed computing strategies in AI environments (multi-GPU, NCCL, MPI). Strong debugging, problem-solving, and performance tuning skills in complex systems. ACADEMIC CREDENTIALS: Bachelor’s or Master’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field. Advanced degrees or published work in HPC, GPU computing, or AI systems is a plus. #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.Senior Software Architect – GPU Kernel Optimization & Distributed AI Systems THE TEAM: Join AMD’s high-impact team at the heart of innovation in AI, ML, and high-performance computing (HPC). We’re a collaborative group of software architects and GPU engineers focused on pushing the boundaries of AI model performance across distributed, GPU-accelerated platforms. Our work drives the next generation of AMD’s AI software stack, enabling large-scale machine learning training and inference workloads in data centers and enterprise environments. THE ROLE: As a Senior Software Developer, you will develop both GPU kernel-level optimization and distributed software efforts for large-scale AI workloads. This is a technical leadership role with direct influence over critical software components in AMD’s AI stack. You’ll architect and implement optimized compute kernels, guide software teams through the full product lifecycle, and work closely with internal and external partners to deploy scalable, high-performance solutions. THE PERSON: We’re looking for a highly skilled, deep systems thinker who thrives in complex problem domains involving parallel computing, GPU architecture, and AI model execution. You are confident leading software architecture decisions and know how to translate business goals into robust, optimized software solutions. You’re just as comfortable writing performance-critical code as you are guiding agile development teams across product lifecycles. Ideal candidates have a strong balance of low-level programming, distributed systems knowledge, and leadership experience—paired with a passion for AI performance at scale. KEY RESPONSIBILITIES: GPU Kernel Optimization: Develop and optimize GPU kernels to accelerate inference and training of large machine learning models while ensuring numerical accuracy and runtime efficiency. Multi-GPU and Multi-Node Scaling: Architect and implement strategies for distributed training/inference across multi-GPU/multi-node environments using model/data parallelism techniques. Performance Profiling: Identify bottlenecks and performance limitations using profiling tools; propose and implement optimizations to improve hardware utilization. Parallel Computing: Design and implement multi-threaded and synchronized compute techniques for scalable execution on modern GPU architectures. Benchmarking & Testing: Build robust benchmarking and validation infrastructure to assess performance, reliability, and scalability of deployed software. Documentation & Best Practices: Produce technical documentation and share architectural patterns, code optimization tips, and reusable components. PREFERRED EXPERIENCE: Software Team Leadership Collaboration with customers and business units to define deliverables and roadmaps. Interfacing with executive leadership on program progress and strategic planning. Experience in production-level software deployment (e.g., upstreaming to open source, commercial rollouts). Software Architecture Deep experience with GPU kernel optimization in C++12/17/20. Working knowledge of frameworks such as PyTorch, vLLM, Cutlass, Kokkos. Practical expertise in CPU/GPU architecture and system-level performance tuning. Proficiency in Python scripting and infrastructure automation. Application of software design patterns and industry-standard engineering practices. GPU & Low-Level Optimization Hands-on experience with CUDA and low-level GPU programming. Kernel optimization in assembly and tight loops for latency-sensitive code. Proficiency with performance profiling tools (Nsight, VTune, Perf, etc.). Experience with distributed computing strategies in AI environments (multi-GPU, NCCL, MPI). Strong debugging, problem-solving, and performance tuning skills in complex systems. ACADEMIC CREDENTIALS: Bachelor’s or Master’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field. Advanced degrees or published work in HPC, GPU computing, or AI systems is a plus. #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.