Model Optimization Engineer (AI)

Location: 100% remote within the United States

Salary: $150,000–$175,000 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 throughput, latency, and cost across model training and inference workloads.
• Improve large neural network systems across the stack, from low-level kernels to distributed systems.
• Apply GPU architecture, model parallelism, memory management, and compiler-level optimization techniques.
• Use instrumentation, profiling, measurement, and debugging to make data-driven optimization decisions.
• Collaborate with product, design, engineering, operations, and business stakeholders to turn ambiguous requirements into production solutions.
• Contribute through code reviews, design reviews, mentoring, and delivery of reliable production work.

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.
• Deep understanding of distributed training and inference, profiling tools, model compression, memory hierarchies, communication primitives, and parallelism strategies.
• Must be authorized to work in the United States as a U.S. citizen, Green Card holder, EAD holder, or H-1B transfer candidate; new H-1B sponsorship is not available.

Nice to have

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

Culture & Benefits

• Full-time direct W-2 employment.
• Career growth opportunities within an established organization.
• Cross-functional collaboration with product, design, engineering, operations, and business stakeholders.