AI Performance Engineer

Location: 100% remote within the United States

Salary: $75,000–$100,000 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 training and inference workloads for large neural network systems to increase throughput, reduce latency, and control costs.
• Improve performance across the stack, from low-level kernels and GPU execution to distributed system configuration.
• Apply instrumentation, profiling, measurement, and debugging to make data-driven optimization decisions.
• Design and tune model parallelism, memory management, communication primitives, and distributed training and inference systems.
• Collaborate with product, design, engineering, operations, and business stakeholders to translate ambiguous requirements into production-ready solutions.
• Contribute through code reviews, design reviews, technical communication, and mentorship of junior engineers.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
• Six or more years of experience in performance engineering, ML systems, or HPC.
• Strong proficiency in Python and C++.
• Hands-on experience optimizing deep learning workloads on modern GPUs.
• Experience with profiling tools across CPU, GPU, and distributed systems, plus strong measurement, debugging, and analytical skills.
• U.S. work authorization is required; new H-1B visa petitions cannot be sponsored.

Nice to have

• Experience optimizing LLM inference at production scale.
• Contributions to vLLM, TensorRT-LLM, DeepSpeed, or similar projects.
• Experience authoring custom kernels in Triton or CUTLASS.
• Experience with FinOps for AI workloads.
• Publications or talks on AI systems performance.

Culture & Benefits

• Full-time direct W-2 employment.
• Opportunity to work on cloud, AI, data, and enterprise solutions.
• Cross-functional collaboration with product, design, engineering, operations, and business stakeholders.
• Career growth opportunities within an established organization.