Software Engineer, 100-120K

AI/ML Development Ames, Iowa, United States

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Summary

I am a Software Engineer with a Masters degree in Computer Science from Virginia Tech and hands-on experience building production-grade AI and data systems in enterprise environments. My work sits at the intersection of machine learning, large language models, cloud engineering, and observability.

At RFA Engineering (on-site at John Deere), I led the development of an internal cross-team observability platform that consolidated multiple APIs into a structured SQL database and delivered real-time analytics through Streamlit dashboards. I engineered an LLM-powered semantic query layer using LangChain and OpenRouter that translated natural language into executable SQL, enabling teams to interact with operational data more intuitively. This significantly improved data accessibility and cross-team efficiency.

I also designed and evaluated object detection systems for complex, real-world image datasets exceeding 800,000 records. Using PySpark on Databricks with AWS S3, I built scalable data pipelines, benchmarked YOLOv5/v8 against proprietary models, and deployed cloud-based experiment tracking and model workflows leveraging AWS services such as S3, RDS, and Lambda. In addition, I owned the automation testing workbench and introduced GitHub Actions-based optimizations that reduced operational costs by approximately $15,000 annually.

Earlier in my career, I contributed to AI research and applied machine learning to real-world challenges, including adversarial attack mitigation, plant species classification, and wildlife monitoring using YOLO-based detection systems for a government-sanctioned conservation project. My academic work has also resulted in peer-reviewed publications in computational intelligence and image recovery.

Overall, my experience reflects a strong foundation in applied AI, scalable data engineering, and production system reliability, with a consistent focus on building intelligent systems that deliver measurable business impact.

Expectations

Im looking for a role where I can work on impactful, production-grade AI systems that solve meaningful business problems. Im particularly interested in opportunities that involve building and deploying machine learning or LLM-based solutions end-to-end from data engineering and model development to evaluation, deployment, and monitoring.

I value teams that emphasize strong engineering practices, measurable impact, and cross-functional collaboration. Continuous learning, technical ownership, and the ability to contribute to scalable, reliable systems are important to me. Im excited about environments that encourage innovation while maintaining high standards for quality and performance.