Description

Senior AI/ML software engineer with 11 years of experience focused on LLM training, evaluation systems, and

agentic infrastructure. I design and build the environments where models are trained, tested, and graded,

including simulation systems, data pipelines, and evaluation frameworks. I have strong applied mathematical

knowledge in probability, statistics, linear algebra, discrete mathematics, and optimization, used directly in model

evaluation design, benchmarking, and problem construction. I also bring hands-on experience across Python,

Rust, JavaScript, TypeScript, Node.js, Docker, and cloud platforms including AWS, GCP, and Azure.

Languages

English
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

Amazon
Senior AI/ML Engineer
March 2020 - December 2025 (5 years and 9 months)
Houston, TX, USA
• • Reviewed and audited complex simulation and training datasets, identifying logical inconsistencies, broken identity flows, invalid JSON structures, and non-executable task definitions before production training.
• • Evaluated and compared model outputs across multiple programming ecosystems (Python, C++, C#, Java, Go, Rust, TypeScript, JavaScript), analyzing correctness, efficiency, and reasoning robustness across different task dimensions.
• • Delivered large-scale RAG systems over ~1M+ documents using FAISS, semantic chunking, and hybrid retrieval strategies, combined with LangChain-based multi-step agents and tool-calling orchestration.
• • Designed and implemented an algorithmic learning model to improve speech by implementing speech synthesis and noise removal.
• • Designed original computer science and machine learning evaluation problems spanning algorithms, distributed systems, databases, networks, probability theory, and theoretical computer science.
• • Built mathematically rigorous problem sets in statistics and number theory that resist trivial solutions via NumPy/SciPy, and verified correctness through full programmatic validation.
BMC Software
AI Engineer
February 2014 - December 2019 (5 years and 10 months)
Houston, TX, USA
• • Applied strong mathematical reasoning (linear algebra, probability theory, statistics, graph theory, and combinatorics) to create evaluation tasks that test deep understanding rather than surface-level pattern matching.
• • Designed grading rubrics that evaluate not only final answers but also reasoning validity, constraint handling, and hidden assumption detection in AI-generated solutions.
• • Maintained distributed ETL/ELT pipelines and integrated LLM-based evaluation components for continuous scoring, monitoring, and dataset enrichment in production workflows.
• • Developed and deployed AI systems on AWS and Azure using Azure ML Studio, Databricks, Docker, and serverless architectures, ensuring scalable and reliable inference pipelines.
• • Integrated AI capabilities into full-stack systems using Python, React, Node.js, and Django, enabling intelligent automation features across enterprise web and mobile platforms.
• •Developed a company employee management and security program by constructing an image processing corpus and realizing modeling.