AI Systems Performance Specialist

Location: 100% remote within the Continental United States

Salary: $130,000–$180,000 annually

Company

hirify.global is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

• Optimize AI training and inference pipelines for throughput, low latency, scalability, reliability, and infrastructure efficiency.
• Improve GPU utilization, memory management, kernel execution, and multi-GPU performance across production workloads.
• Implement quantization, pruning, mixed precision, batching, caching, speculative decoding, and model parallelism.
• Profile applications across compute, memory, networking, and storage to identify and resolve bottlenecks.
• Optimize distributed training and inference using frameworks such as NCCL, DeepSpeed, PyTorch Distributed, Ray, and MPI.
• Build benchmarking frameworks, performance dashboards, monitoring solutions, and regression testing pipelines while mentoring engineering teams.

Requirements

• 10+ years of professional experience in performance engineering, AI infrastructure, machine learning systems, HPC, or distributed computing.
• Bachelor’s or Master’s degree in computer science, computer engineering, electrical engineering, artificial intelligence, or a related discipline.
• Expert-level Python and C++ programming skills with extensive CUDA and GPU-accelerated AI workload optimization experience.
• Strong knowledge of LLMs, deep learning frameworks, model serving, production AI inference, distributed systems, networking, and storage optimization.
• Experience with NVIDIA Nsight Systems, Nsight Compute, PyTorch Profiler, TensorBoard, or similar tools, and with AWS, Azure, or GCP.
• Applicants must be U.S. citizens, Green Card holders, EAD holders, or H-1B transfer candidates; new H-1B sponsorship is not available.

Nice to have

• Production-scale LLM inference and large foundation model serving experience.
• Experience with vLLM, TensorRT-LLM, DeepSpeed, Triton Inference Server, CUTLASS, or FasterTransformer.
• Knowledge of model compression, KV cache optimization, speculative decoding, and advanced inference techniques.
• FinOps experience, AI systems research, open-source contributions, patents, or technical publications.
• Familiarity with AMD ROCm, Intel oneAPI, or custom AI accelerator technologies.

Culture & Benefits

• Full-time direct W-2 employment.
• Opportunity to work on enterprise-scale cloud, AI, data, and infrastructure solutions.
• Collaboration with AI researchers, ML engineers, platform engineers, and infrastructure teams.
• Career growth opportunities within an established technology organization.