GPU Kernel Performance Engineer Job at AMD (Beijing)

Member of Technical Staff, Performance Optimization

We're looking for a Software Engineer focused on Performance Optimization to hel...

Location

United States , San Mateo

Salary:

175000.00 - 220000.00 USD / Year

Fireworks AI

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience
5+ years of experience working on performance optimization or high-performance computing systems
Proficiency in CUDA or ROCm and experience with GPU profiling tools (e.g., Nsight, nvprof, CUPTI)
Familiarity with PyTorch and performance-critical model execution
Experience with distributed system debugging and optimization in multi-GPU environments
Deep understanding of GPU architecture, parallel programming models, and compute kernels

Job Responsibility

Optimize system and GPU performance for high-throughput AI workloads across training and inference
Analyze and improve latency, throughput, memory usage, and compute efficiency
Profile system performance to detect and resolve GPU- and kernel-level bottlenecks
Implement low-level optimizations using CUDA, Triton, and other performance tooling
Drive improvements in execution speed and resource utilization for large-scale model workloads (LLMs, VLMs, and video models)
Collaborate with ML researchers to co-design and tune model architectures for hardware efficiency
Improve support for mixed precision, quantization, and model graph optimization
Build and maintain performance benchmarking and monitoring infrastructure
Scale inference and training systems across multi-GPU, multi-node environments
Evaluate and integrate optimizations for emerging hardware accelerators and specialized runtimes

What we offer

Meaningful equity in a fast-growing startup
Competitive salary
Comprehensive benefits package

Fulltime

New

Software Development Engineer

As a core member of the team, you will play a pivotal role in optimizing and dev...

Location

China , Shanghai

Salary:

Not provided

AMD

Expiration Date

Until further notice

Requirements

Bachelor’s and/or Master’s Degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
5+ years of professional experience in technical software development, with a focus on GPU optimization, performance engineering, and framework development
Skilled engineer with strong technical and analytical expertise in C++ development within Linux environments
Strong problem-solving skills, a proactive approach, and a keen understanding of software engineering best practices are essential
GPU Kernel Development & Optimization: Experienced in designing and optimizing GPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly (ASM)
Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming
Leveraging tools like Compute Kernel (CK), CUTLASS, and Triton for multi-GPU and multi-platform performance
Deep Learning Integration: Experienced in integrating optimized GPU performance into machine learning frameworks (e.g., TensorFlow, PyTorch) to accelerate model training and inference
Software Engineering: Skilled in Python and C++
Experience in debugging, performance tuning, and test design

Job Responsibility

Optimize Deep Learning Frameworks: Enhance and optimize frameworks like TensorFlow and PyTorch for AMD GPUs in open-source repositories
Develop GPU Kernels: Create and optimize GPU kernels to maximize performance for specific AI operations
Develop & Optimize Models: Design and optimize deep learning models specifically for AMD GPU performance
Collaborate with GPU Library Teams: Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs
Collaborate with Open-Source Maintainers: Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream
Work in Distributed Computing Environments: Optimize deep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems
Utilize Cutting-Edge Compiler Tech: Leverage advanced compiler technologies to improve deep learning performance
Optimize Deep Learning Pipeline: Enhance the full pipeline, including integrating graph compilers
Software Engineering Best Practices: Apply sound engineering principles to ensure robust, maintainable solutions

What we offer

AMD benefits at a glance

New

Software Development Engineer

As a core member of the team, you will play a pivotal role in optimizing and dev...

Location

China , Shanghai

Salary:

Not provided

AMD

Expiration Date

Until further notice

Requirements

Bachelor’s and/or Master’s Degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
5+ years of professional experience in technical software development, with a focus on GPU optimization, performance engineering, and framework development
Skilled engineer with strong technical and analytical expertise in C++ development within Linux environments
Strong problem-solving skills, a proactive approach, and a keen understanding of software engineering best practices
Experience in GPU Kernel Development & Optimization for deep learning on AMD GPUs using HIP, CUDA, and assembly (ASM)
Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming
Experience leveraging tools like Compute Kernel (CK), CUTLASS, and Triton for multi-GPU and multi-platform performance
Experience in Deep Learning Integration into machine learning frameworks (e.g., TensorFlow, PyTorch) to accelerate model training and inference
Skilled in Python and C++, with experience in debugging, performance tuning, and test design
Solid experience in running large-scale workloads on heterogeneous compute clusters

Job Responsibility

Optimize Deep Learning Frameworks: Enhance and optimize frameworks like TensorFlow and PyTorch for AMD GPUs in open-source repositories
Develop GPU Kernels: Create and optimize GPU kernels to maximize performance for specific AI operations
Develop & Optimize Models: Design and optimize deep learning models specifically for AMD GPU performance
Collaborate with GPU Library Teams: Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs
Collaborate with Open-Source Maintainers: Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream
Work in Distributed Computing Environments: Optimize deep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems
Utilize Cutting-Edge Compiler Tech: Leverage advanced compiler technologies to improve deep learning performance
Optimize Deep Learning Pipeline: Enhance the full pipeline, including integrating graph compilers
Software Engineering Best Practices: Apply sound engineering principles to ensure robust, maintainable solutions

What we offer

Benefits offered are described: AMD benefits at a glance

New

Sr. Software Development Engineer

As a core member of the team, you will play a pivotal role in optimizing and dev...

Location

China , Shanghai

Salary:

Not provided

AMD

Expiration Date

Until further notice

Requirements

Skilled engineer with strong technical and analytical expertise in C++ development within Linux environments
Ability to define goals, manage development efforts, and deliver high-quality solutions
Strong problem-solving skills
Proactive approach
Keen understanding of software engineering best practices
Experience in GPU kernel development & optimization for AMD GPUs using HIP, CUDA, and assembly (ASM)
Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming
Experience leveraging tools like Compute Kernel (CK), CUTLASS, and Triton for multi-GPU and multi-platform performance
Experience in integrating optimized GPU performance into machine learning frameworks (e.g., TensorFlow, PyTorch)
Skilled in Python and C++

Job Responsibility

Optimize Deep Learning Frameworks: Enhance and optimize frameworks like TensorFlow and PyTorch for AMD GPUs in open-source repositories
Develop GPU Kernels: Create and optimize GPU kernels to maximize performance for specific AI operations
Develop & Optimize Models: Design and optimize deep learning models specifically for AMD GPU performance
Collaborate with GPU Library Teams: Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs
Collaborate with Open-Source Maintainers: Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream
Work in Distributed Computing Environments: Optimize deep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems
Utilize Cutting-Edge Compiler Tech: Leverage advanced compiler technologies to improve deep learning performance
Optimize Deep Learning Pipeline: Enhance the full pipeline, including integrating graph compilers
Software Engineering Best Practices: Apply sound engineering principles to ensure robust, maintainable solutions

Member of Technical Staff - GPU Performance Engineer

Our models and workflows require performance work that generic frameworks don’t ...

Location

United States , San Francisco; Boston

Salary:

Not provided

Liquid AI

Expiration Date

Until further notice

Requirements

Authored custom CUDA kernels (not only calling cuDNN/cuBLAS)
Strong understanding of GPU architecture and performance: memory hierarchy, warps, shared memory/register pressure, bandwidth vs compute limits
Proficiency with low-level profiling (Nsight Systems/Compute) and performance methodology
Strong C/C++ skills

Job Responsibility

Write high-performance GPU kernels for our novel model architectures
Integrate kernels into PyTorch pipelines (custom ops, extensions, dispatch, benchmarking)
Profile and optimize training and inference workflows to eliminate bottlenecks
Build correctness tests and numerics checks
Build/maintain performance benchmarks and guardrails to prevent regressions
Collaborate closely with researchers to turn promising ideas into shipped speedups

What we offer

Competitive base salary with equity in a unicorn-stage company
We pay 100% of medical, dental, and vision premiums for employees and dependents
401(k) matching up to 4% of base pay
Unlimited PTO plus company-wide Refill Days throughout the year

Fulltime

New

Software Development Engineer

As a core member of the team, you will play a pivotal role in optimizing and dev...

Location

China , Shanghai

Salary:

Not provided

AMD

Expiration Date

Until further notice

Requirements

Master’s or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related fields
5+ years of professional experience in technical software development, with a focus on GPU optimization, performance engineering, and framework development
Skilled engineer with strong technical and analytical expertise in C++ development within Linux environments
Strong problem-solving skills, a proactive approach, and a keen understanding of software engineering best practices
GPU Kernel Development & Optimization: Deep experienced in designing and optimizing GPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly (ASM)
Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming
Deep Learning Integration: Strong experienced in integrating optimized GPU performance into machine learning and LLM frameworks (e.g., vLLM, SGlang,TensorFlow, PyTorch)
End to end solution optimization: Understand the latest market trend of LLM and multimodal, solid hands-on E2E performance tuning experience on distributed inference (e.g, P/D disaggregation and Large-EP) and RL
Software Engineering: Skilled in Python and C++, with experience in debugging, performance tuning, and test design
High-Performance Computing: Expert experienced in running large-scale workloads on heterogeneous computing clusters

Job Responsibility

End to end optimization: Build and optimize end to end distributed inference (e.g, P/D disaggregation and Large-EP) and RL solutions on mainstream frameworks like vLLM and SGlang
Collaborate with GPU Library Teams: Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs
Collaborate with Open-Source Maintainers: Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream
Work in Distributed Computing Environments: Optimize deep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems
Utilize Cutting-Edge Compiler Tech: Leverage advanced compiler technologies to improve deep learning performance
Optimize Deep Learning Pipeline: Enhance the full pipeline, including integrating graph compilers
Software Engineering Best Practices: Apply sound engineering principles to ensure robust, maintainable solutions

What we offer

AMD benefits at a glance

New

GPU Performance Attainment Engineer

As a senior member of the pre-silicon performance attainment team, you will be a...

Location

India , Hyderabad

Salary:

Not provided

AMD

Expiration Date

Until further notice

Requirements

Several years of experience in GPU pre-silicon performance analysis and debug
Proficiency with performance modeling and simulation tools
Strong understanding of GPGPU programming APIs and Machine Learning workloads
Expertise in C/C++ /Scripting (Python, Perl, Shell etc.)
Experience with hardware description languages such as Verilog is a plus
Familiarity with the software stack is a plus, preferably related to GPUs—such as applications, drivers, compilers, and firmware
Bachelor's or higher degree in Computer Science, Electrical Engineering, or a closely related field

Job Responsibility

Debug performance issues and analyze data from the full-chip Emulation Platform, RTL Simulator, and Architecture and Roofline Models
Analyze model projection results and identify algorithm issues to find novel solutions for improving the accuracy of projection for different families of products, and over multiple generations
Get performance projections for kernels using an analytical model
Identify technical problems, break them down, summarize multiple possible solutions, and help the team to make progress
Automate processes related to performance infrastructure and data collection tasks, to enhance productivity and refine processes for improved efficiency
Engage with the workloads team to acquire and align on required workloads, run the selected workload traces on the performance simulator, analyze the performance results and metrics to root cause any anomalies
Collaborate with simulator team to bridge gaps between the performance numbers and the performance targets
Influence design trade-offs and optimizations by working closely with compiler, driver, library, and hardware engineers to achieve the highest performance for selected workloads
Innovate new algorithmic improvements that exploit the strengths of the hardware architecture to deliver the best possible machine learning performance

Founding GPU Kernel Engineer

We're looking for a Founding GPU Kernel Engineer who lives right at the boundary...

Location

United States , San Francisco

Salary:

285000.00 - 315000.00 USD / Year

YC Work at a Startup

Expiration Date

Until further notice

Requirements

Deep expertise in GPU architecture
Proven track record of hand-writing kernels that match or beat vendor libraries (cuBLAS, cuDNN, CUTLASS)
Strong skills with low-level profiling tools: Nsight Compute, Nsight Systems, rocprof, or equivalents
Experience reading and reasoning about PTX/SASS or GPU assembly
Solid systems programming in C++ and CUDA (or ROCm/HIP)
Good understanding of how high-level ML operations map to hardware execution
Experience with distributed training systems: collective ops like all-reduce and all-gather, NCCL/RCCL, multi-node communication patterns

Job Responsibility

Write and hand-optimize GPU kernels for ML workloads (matmuls, attention, normalization, etc.) to set the performance ceilings
Profile at the microarchitectural level: look into SM utilization, warp stalls, memory bank conflicts, register pressure, instruction throughput
Debug performance issues by digging deep into things like clock speeds, thermal throttling, driver behavior, hardware errata
Turn your hand-optimization insights into automated compiler passes (working closely with our compiler team)
Develop performance models that predict how kernels will behave across different GPU architectures
Build tools and methods for systematic kernel optimization
Work with NVIDIA, AMD, and emerging AI accelerators - understand the common parts and what's vendor-specific

What we offer

bonus
equity
benefits
relocation assistance

Fulltime

GPU Kernel Performance Engineer

AMD

Location:
China , Beijing

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
March 19, 2026

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