layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

LAYIQ - Software Design Engineer - GPU Kernel Optimization at AMD

Responsibilities

THE ROLE:

As a senior technical member of the team, you will play a key role in designing, developing, and optimizing high-performance GPU kernels for LLM and other ML models. You will analyze performance bottlenecks and develop architecture-aware optimizations to maximize compute efficiency, memory bandwidth utilization, and overall GPU performance.

You will also collaborate closely with GPU architecture, compiler, library, and framework teams to develop scalable solutions and advance GPU performance across current and next-generation platforms.

THE PERSON:

The ideal candidate has strong experience in GPU programming, performance analysis and system software development. You will provide technical leadership, guiding teams and driving projects/initiatives independently. You will define goals, scope, and own development efforts while collaborating effectively within a high-performing team.

KEY RESPONSIBILITIES:

Architect and Optimize AI Workloads: Lead the optimization of LLMs, quantized models, and emerging AI workloads for AMD GPU architectures.
Develop High-Performance GPU Kernels: Design, implement, profile, and optimize GPU kernels, with a strong focus on maximizing hardware utilization and application performance.
Drive Performance Analysis: Perform deep performance characterization across compute, memory bandwidth, cache hierarchy, synchronization, kernel scheduling, and execution efficiency to identify and eliminate bottlenecks.
Advance Compiler and Code-Generation Technologies: Develop compiler-level optimizations and code-generation techniques using LLVM, MLIR, and related technologies to achieve portable and scalable GPU performance.
Innovate with AI-Assisted Development: Build AI-powered coding agents and automation workflows for kernel generation, optimization, benchmarking, and validation.
Collaborate with model and infrastructure teams to improve end-to-end AI system performance.
PREFERRED EXPERIENCE: Strong C++ and/or Python skills
Solid understanding of GPU compute, memory hierarchy, cache behavior, synchronization, and performance bottlenecks.
Strong experience developing and optimizing GPU kernels using HIP, CUDA, C/C++, or similar technologies.
Strong analytical/problem-solving skills and pronounced attention to details
Must be a self-starter, and able to independently drive tasks to completion
ACADEMIC CREDENTIALS: Bachelors or Masters degree in computer engineering, computer science or a related field
This role is not eligible for visa sponsorship.

Software Design Engineer - GPU Kernel Optimization

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