AI Performance Optimization Engineer

Location: 100% remote within the Continental United States

Salary: $100,000–$150,000 per year, plus benefits

Company

hirify.global is a software development company building scalable, secure, and user-friendly solutions that automate and optimize business operations.

What you will do

• Profile and optimize AI training and inference pipelines for throughput, latency, and cost.
• Identify bottlenecks across data loading, model computation, communication, memory, and storage access.
• Implement quantization, sparsity, pruning, KV-cache optimization, continuous batching, and speculative decoding for efficient model serving.
• Optimize distributed training with tensor parallelism, pipeline parallelism, FSDP, and ZeRO-style sharding.
• Drive compiler and kernel-level optimization using Triton, XLA, TorchInductor, or TVM.
• Build benchmark and regression frameworks, evaluate new hardware and software, and document performance-tuning practices.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
• At least six 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, inference, profiling, memory hierarchies, communication primitives, and parallelism strategies.
• Strong measurement, debugging, analytical reasoning, communication, and collaboration skills.

Nice to have

• Production-scale LLM inference optimization experience.
• Contributions to vLLM, TensorRT-LLM, DeepSpeed, or similar projects.
• Experience with custom kernels in Triton or CUTLASS.
• Experience with FinOps for AI workloads or publications and talks on AI systems performance.

Culture & Benefits

• Full-time, direct W2 employment with hirify.global.
• Long-term, multi-year in-house Statement of Work engagement.
• Benefits and career growth opportunities.
• Collaboration with product, design, engineering, operations, and business stakeholders.
• Mentorship, code reviews, design reviews, and knowledge sharing across engineering teams.

Hiring process

• A technical coding assessment is mandatory.
• Qualified candidates may apply with a resume.
• No new H1B sponsorship is available; valid H1B transfer candidates are welcome and transfer support is available.