Responsibilities
• Guide research and engineering teams to close knowledge gaps and improve AI model performance in systems-level optimization, compiler engineering, and runtime performance topics
• Design challenging, domain-relevant tasks across multiple specializations and write accurate, well-structured solutions to performance engineering and systems programming problems
• Evaluate performance engineering tasks and solutions and provide clear, written technical feedback
• Develop guidelines and detailed rubrics/evaluation frameworks to assess systems design quality, profiling methodology, memory optimization, and performance analysis across AI workloads
• Collaborate with other subject matter experts to ensure consistency and accuracy in training data

Requirements
• 2+ years of dedicated professional experience in performance engineering, systems programming, or low-level optimization
• Deep hands-on expertise in C++ for performance-critical systems
• Proficiency in Python for profiling, benchmarking, and tooling workflows; experience with Rust in systems-level or safety-critical performance contexts is a strong plus
• Demonstrable track record of measurable performance improvements on production systems (e.g., latency reduction, throughput gains, memory footprint optimization)
• Demonstrable career progression
• Ability to engage reliably for at least 30 hours per week during weekdays
• Strong written communication skills and ability to explain complex technical decisions clearly

How to Apply
Click "Apply" to be taken to the Cincinnatus LLC application. Cincinnatus serves as the employer of record providing W-2 employment, payroll, benefits, and compliance while placing employees directly within client teams. Applying through our link supports WFH Bulletin as a referral partner, but you are welcome to apply directly if you prefer.