I’m an applied AI developer with 7+ years of hands-on machine learning experience, including senior-level work embedded within NASA’s High End Computing (HECC) program. I specialize in turning complex, messy data into reliable, scalable AI systems—not just demos.
I work across:
• Deep learning (PyTorch, TensorFlow, CNNs, RNNs/GRUs, Transformers)
• End-to-end ML pipelines (from raw data to evaluation and deployment)
• Large-scale & multi-GPU training
• Model debugging, optimization, and performance tuning
Before AI, I spent over 20 years in experimental science and earned a PhD in Chemistry, which means I approach ML problems with rigor, validation, and a strong understanding of real-world constraints.
I’m especially effective when:
• the problem isn’t fully defined yet,
• the data is large, noisy, or scientific/technical,
• or performance and correctness actually matter.
Clients work with me as a senior technical partner, not just an implementer. I communicate clearly, move quickly, and focus on building AI that holds up outside the notebook.
Let’s build something that actually works.
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