Presentation
5+ years of experience designing, evaluating, and improving AI systems. Strong command of Python (NumPy, Pandas, SciPy)
for numerical validation, simulation, and verification of computational results. Experienced in assessing AI-generated
solutions for correctness, hidden assumptions, and constraint violations, and in building structured evaluation and scoring
frameworks for multi-step technical problems. Background spans LLM-driven applications, classical machine learning, and
production engineering, with a consistent focus on rigor, reproducibility, and industry-standard reasoning. Comfortable
collaborating with distributed, research-oriented teams to uphold high scientific and technical integrity.

