Software Engineer, GPU Performance

We Love AI Jobs; Los Angeles, Northern (CA, KY); Hybrid; USD 120,000 - 170,000; Full time

Job summary

HeyGen is seeking a Software Engineer focused on GPU performance to accelerate the speed and efficiency of AI video products. You will profile model execution and inference, implement optimizations, and collaborate with researchers and infrastructure teams to bring improvements into production.

The role emphasizes profiling tools, kernel optimization, and measurable reductions in latency and cost while maintaining output quality.

Qualifications

• Experience optimizing GPU-based AI workloads or high-performance computing systems.
• Proficiency in Python and PyTorch; able to profile and optimize GPU kernels.
• Familiarity with GPU hardware details such as memory bandwidth and tensor cores.

Responsibilities

• Profile GPU workloads to identify bottlenecks in model execution and inference.
• Improve latency, throughput, and GPU utilization through batching and scheduling.
• Develop benchmarks and regression tests to track performance.
• Collaborate with researchers and infrastructure engineers to deploy optimizations.
• Measure impact on latency, throughput, and cost.

Skills

Python

PyTorch

GPU profiling

CUDA

Triton

PyTorch Profiler

Tools

NVIDIA Nsight Systems

NVIDIA Nsight Compute

CUDA

Triton

PyTorch Profiler

Job description

# Software Engineer, GPU PerformanceHeyGenLos Angeles, Palo Alto, San Francisco, Toronto, SingaporeFull-timeAI tools:PyTorchCUDAUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageYou’ll optimize the GPU performance of HeyGen’s AI video products, including avatar and video translation experiences. The work spans profiling model execution and inference, implementing performance improvements, and collaborating with researchers and infrastructure engineers to bring them into production.* Permanent* On-site### Skills and expertisePythonPyTorchGPU profilingNVIDIA Nsight SystemsNVIDIA Nsight ComputePyTorch ProfilerCUDATriton### Key responsibilities* Profile GPU workloads to find bottlenecks in model execution, preprocessing, and inference serving.* Improve latency, throughput, and GPU utilization through scheduling, batching, and memory management.* Build benchmarks and collaborate with research and infrastructure teams to deploy optimizations.## How this job comparesCompared with 329 open mid-level machine learning jobs on October 10, 2026.Similar open jobs: We Love AI Jobs lists 329 open mid-level machine learning jobs at 145 companies.Remote work: This job is on site. 66 of the 329 mid-level machine learning jobs (20%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. The role directly optimizes AI model execution and inference infrastructure for HeyGen’s AI video applications. Profiling and improving GPU-based AI workloads are central to the job.## Full descriptionAbout HeyGenAt HeyGen, our mission is to make visual storytelling accessible to all. Over the last decade, visual content has become the preferred method of information creation, consumption, and retention. But the ability to create such content, in particular videos, continues to be costly and challenging to scale. Our ambition is to build technology that equips more people with the power to reach, captivate, and inspire audiences.Learn more at www.heygen.com. Visit our Mission and Culture doc here.Position SummaryHeyGen is building AI applications including Avatar IV, Photo Avatar, Interactive Avatar, and Video Translation. We’re looking for a Software Engineer focused on GPU performance to make the systems behind these experiences faster and more efficient.You will work across model execution and inference infrastructure, using profiling and measurement to improve latency, throughput, and GPU cost. This role is a fit for an engineer who enjoys understanding how software uses the hardware beneath it.Key Responsibilities• Use NVIDIA Nsight Systems, Nsight Compute, and PyTorch Profiler to investigate GPU utilization, kernel execution, memory bandwidth, and CPU–GPU data movement.• Identify bottlenecks across model execution, preprocessing, and inference serving, then measure the impact of each optimization.• Improve performance through batching, scheduling, memory management, and better GPU utilization.• Develop or integrate high-performance GPU kernels when existing implementations limit performance.• Build benchmarks and automated checks that catch performance regressions across representative video workloads.• Collaborate with AI researchers and infrastructure engineers to bring optimizations into production.• Measure the effect of changes on latency, throughput, cost, and output quality.Qualifications• Experience optimizing GPU-based AI workloads or high-performance computing systems.• Proficiency in Python and experience with PyTorch or a similar machine learning framework.• Strong curiosity about GPU hardware, including memory bandwidth, cache behavior, tensor cores, and data movement between CPU and GPU.• Experience using profiling tools to connect hardware behavior to application-level bottlenecks and validate improvements.• Ability to turn performance experiments into reliable production changes and communicate tradeoffs clearly.Preferred Qualifications• Experience with CUDA, Triton, or C++ GPU programming.• Experience optimizing video, image, audio, diffusion, or Transformer models.• Familiarity with multi-GPU inference, GPU interconnects, quantization, or large-scale model serving.• Experience building performance benchmarks or regression testing infrastructure.• Prior experience in a fast-paced technology environment.What HeyGen Offers• Competitive salary and benefits package.• Dynamic and inclusive work environment.• Opportunities for professional growth and advancement.• Collaborative culture that values innovation and creativity.• Access to the latest technologies and tools.HeyGen is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.