Raytonne Lusi

Mechanical Engineer with over four years of professional experience in applying first principles of engineering, numerical analysis, and Python-based validation for real-world mechanical systems. Experienced in creating graduate/industry-level problems in engineering, analyzing multi-step analytical solutions, and validating results by applying Python. Demonstrated capability in assessing assumptions, constraints, and logic in AI-generated results.

Fluent in written English (C1/C2 proficiency level). Experienced in remote work environments.

Mechanical Engineer at Atlantic Mechanical Solutions LLC (2020-01 – 2024-12)

Conducted analytical and numerical analyses of mechanical systems and verified engineering calculations

• Conducted analytical and numerical analyses of mechanical systems, which include thermal systems, fluid flow, and mechanical components.
• Verified the results of analytical work through Python scripts, which include NumPy and SciPy, for numerical accuracy and boundary condition verification.
• Verified the accuracy of various engineering calculations in terms of correctness, assumptions, practicality, and conformity to various engineering standards.
• Conducted stress, efficiency, and performance evaluations of various mechanical designs.
• Created detailed technical reports that include methodologies, assumptions, and results.
• Worked remotely as a member of a multidisciplinary team to meet strict deadlines.

Mechanical Engineering AI Trainer at Freelance

Developed graduate-level and industry-level mechanical engineering problems and verified AI solutions

• Developed graduate-level and industry-level mechanical engineering problems based on actual engineering practices.
• Verified the solutions provided by AI for their accuracy, logical flow, physical assumptions, and dimensional consistency.
• Utilized structured scoring rubrics to evaluate multi-step reasoning and accuracy of results.
• Used Python programming to validate the results provided by the AI for the analytical and numerical solutions to the problems.
• Identified systematic reasoning flaws in the results provided by the AI and offered corrective feedback based on first principles.
• Worked in an asynchronous manner with reviewers from around the world, engineers, and quality teams.

Bachelor of Science in Mechanical Engineering – University of Central Florida (UCF) (2016-01 – 2020-12)