Performance Optimization Engineer for AI Infrastructure

Fireworks AI

San Mateo (CA)

On-site

USD 180,000 - 260,000

Full time

11 hours ago
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Job summary

Fireworks AI is seeking a Software Engineer focused on Performance Optimization to push the speed and efficiency of our AI infrastructure. You will own optimizations from GPU kernels to large-scale distributed systems, targeting LLMs, VLMs, and video models.

You’ll collaborate with researchers to tune architectures for hardware efficiency, improve memory and compute utilization, and help scale production-grade AI workloads across multi-GPU environments.

Qualifications

  • 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.

Responsibilities

  • 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.

Skills

CUDA
Profiling
PyTorch
Distributed systems
GPU architecture

Education

Bachelor's degree in CS/CE/EE

Tools

Nsight
nvprof
CUPTI
Triton

Job description

Fireworks AI is seeking a Software Engineer focused on Performance Optimization to push the speed and efficiency of our AI infrastructure. You will own optimizations from GPU kernels to large-scale distributed systems, targeting LLMs, VLMs, and video models.

You’ll collaborate with researchers to tune architectures for hardware efficiency, improve memory and compute utilization, and help scale production-grade AI workloads across multi-GPU environments.

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