Product Application Engineer

Advanced Micro Devices; Milano; In loco; EUR 60.000 - 90.000; Tempo pieno

Descrizione del lavoro

A leading technology company in Milan is seeking an AI Product Management professional to enhance product innovation in the field of artificial intelligence. The ideal candidate will oversee GPU kernel development for AI/ML workloads, analyze performance, and collaboratively work with engineering teams to integrate optimized solutions. A BS in a relevant field is required, with a preference for candidates holding an MS and having experience in GPU programming and AI models.

Servizi

Competitive benefits package

Competenze

• Deep knowledge of Data Center AI workloads including LLM and Generative AI.
• Hands-on experience with AI models, end-to-end pipelines, and industry frameworks.
• Strong proficiency in C++ and parallel computing.

Mansioni

• Design, implement, and optimize high-performance GPU kernels for AI workloads.
• Analyze and optimize kernel execution for latency and throughput.
• Evaluate end-to-end performance impact of kernels on AI models.
• Use GPU profiling tools to identify performance inefficiencies.
• Collaborate with software stack teams to expose optimized kernels.

Conoscenze

GPU Architecture Mastery

Kernel Programming Expertise

Performance Engineering

Systems Knowledge

Python DSLs & Triton

Inference Engine Experience

Deep Learning Frameworks

Hardware Agnosticism

Formazione

BS required; MS preferred

Strumenti

NVIDIA CUDA

AMD HIP

OpenAI Triton

TensorRT-LLM

Descrizione del lavoro

Overview

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. We push the limits of innovation to solve the world’s most important challenges and shape the future of AI and beyond. Together, we advance your career.

The Role

Join a team of AI software product management professionals who are passionate about driving product innovation and defining the future of AI-powered solutions. You will oversee the product lifecycle from ideation to market launch, ensuring seamless integration with diverse platforms, including on-premise deployments and leading cloud services. Collaborate with AI engineering and business units to develop cutting-edge AI solutions across applications such as large language model platforms, recommendation systems, natural language processing, and vision recognition.

The Person

Success in this role will require deep knowledge of Data Center AI workloads such as LLM, Generative AI, Recommendation, NLP, Video Analytics, and transformer AI across cloud, client, and edge. Hands-on experience with various AI models, end-to-end pipelines, industry frameworks/SDKs, and solutions is required.

Key Responsibilities

• High-Performance Kernel Development: Design, implement, and optimize high-performance GPU kernels for AI/ML workloads to maximize hardware utilization.
• Performance Optimization: Analyze and optimize kernel execution for latency and throughput, addressing bottlenecks in memory bandwidth, instruction latency, and thread divergence.
• Workload Analysis: Evaluate end-to-end performance impact of kernels on full-stack AI models, ensuring micro-optimizations translate to application-level speedups.
• Profiling & Tuning: Use GPU profiling tools (e.g., ROCm Profiler, Pytorch Profiler) to identify performance cliffs, stall pipelines, and memory hierarchy inefficiencies.
• Architecture Adaptation: Tailor implementation strategies to leverage features of modern GPU architectures (e.g., Matrix Cores, HBM characteristics).
• Framework Integration: Collaborate with software stack teams to expose optimized kernels within high-level frameworks and inference engines.

Preferred Experience

• GPU Architecture Mastery: In-depth understanding of modern GPU architectures, including SMs/CUs, memory hierarchy, and warp/wavefront execution models.
• Kernel Programming Expertise: Strong proficiency in C++ and parallel computing, with hands-on experience in NVIDIA CUDA or AMD HIP kernel programming.
• Performance Engineering: Ability to debug and profile complex GPU workloads, interpreting low-level metrics to drive architectural optimizations.
• Systems Knowledge: Familiarity with asynchronous execution, stream management, and host-device memory transfers.
• Python DSLs & Triton: Experience implementing kernels using OpenAI Triton or other Python-based DSLs for agile kernel development and auto-tuning.
• Inference Engine Experience: Hands-on experience integrating custom kernels into large-scale inference frameworks such as vLLM, SGLang, or TensorRT-LLM.
• Deep Learning Frameworks: Familiarity with writing custom extensions or operators for PyTorch (C++/CUDA extensions).
• Hardware Agnosticism: Experience porting kernels between NVIDIA and AMD architectures or working with cross-platform HPC libraries.

Academic Credentials

• BS required. MS preferred with several years of relevant industry experience.

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 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 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 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 guidance on Responsible AI is available.

This posting is for an existing vacancy.