Remote Performance Engineer for AI Systems Optimization

Hire Feed; Dubai; On-site; AED 354,000 - 557,000; Full time

Job summary

Hire Feed is seeking a Performance Engineer to contribute to cutting-edge AI model training and inference infrastructure. This remote, contract role focuses on hands-on optimization across C++, Python, and Rust to elevate systems performance and reliability.

You will work with a leading AI lab to deliver measurable improvements in latency, throughput, and memory footprint, while shaping evaluation rubrics and guidelines for AI workloads.

Qualifications

• 2+ years of professional experience in performance engineering, systems programming, or low-level optimization.
• Deep hands-on expertise in at least one of C++, Python, or Rust with working familiarity across the others.
• Measurable performance improvements on production systems (latency, throughput, memory footprint).
• Experience writing and assessing performance-engineering tasks for AI model training and evaluation.
• Ability to develop guidelines and rubrics for evaluating systems design quality in AI workloads.

Responsibilities

• Guide research and engineering teams to improve AI model performance in systems-level optimization, compiler engineering, and runtime performance.
• Design challenging tasks across multiple specializations and write accurate solutions to performance engineering problems.
• Evaluate performance engineering tasks and solutions, providing clear, written technical feedback.
• Develop guidelines and evaluation frameworks to assess systems design quality across AI workloads.
• Collaborate with subject matter experts to ensure consistency and accuracy in training data for frontier AI systems.

Skills

Performance engineering

C++

Python

Rust

Job description

Hire Feed is seeking a Performance Engineer to contribute to cutting-edge AI model training and inference infrastructure. This remote, contract role focuses on hands-on optimization across C++, Python, and Rust to elevate systems performance and reliability.

You will work with a leading AI lab to deliver measurable improvements in latency, throughput, and memory footprint, while shaping evaluation rubrics and guidelines for AI workloads.