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Hi, I’m Cameron Wood, a Senior AI/ML Engineer with a track record of designing and delivering mission-focused AI/ML systems for research and government-adjacent projects. I specialize in PyTorch, TensorFlow, and production-ready ML pipelines, and I enjoy turning complex ideas into scalable, cloud-native solutions using AWS, Kubernetes, and robust DevSecOps practices. I lead data curation, feature engineering, and reproducible data versioning with lakeFS, while aligning experiments with STAC metadata standards and maintainable runbooks. I’m passionate about mentoring teammates, strengthening CI/CD, and collaborating with security and audits teams to ensure compliant, reliable deployments across multi-project environments.…Hi, I’m Cameron Wood, a Senior AI/ML Engineer with a track record of designing and delivering mission-focused AI/ML systems for research and government-adjacent projects. I specialize in PyTorch, TensorFlow, and production-ready ML pipelines, and I enjoy turning complex ideas into scalable, cloud-native solutions using AWS, Kubernetes, and robust DevSecOps practices. I lead data curation, feature engineering, and reproducible data versioning with lakeFS, while aligning experiments with STAC metadata standards and maintainable runbooks. I’m passionate about mentoring teammates, strengthening CI/CD, and collaborating with security and audits teams to ensure compliant, reliable deployments across multi-project environments.

Cameron Wood

AI Engineer, Data Scientist, Full Stack Developer, +4

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Hi, I’m Cameron Wood, a Senior AI/ML Engineer with a track record of designing and delivering mission-focused AI/ML systems for research and government-adjacent projects. I specialize in PyTorch, TensorFlow, and production-ready ML pipelines, and I enjoy turning complex ideas into scalable, cloud-native solutions using AWS, Kubernetes, and robust DevSecOps practices. I lead data curation, feature engineering, and reproducible data versioning with lakeFS, while aligning experiments with STAC metadata standards and maintainable runbooks. I’m passionate about mentoring teammates, strengthening CI/CD, and collaborating with security and audits teams to ensure compliant, reliable deployments across multi-project environments.…Hi, I’m Cameron Wood, a Senior AI/ML Engineer with a track record of designing and delivering mission-focused AI/ML systems for research and government-adjacent projects. I specialize in PyTorch, TensorFlow, and production-ready ML pipelines, and I enjoy turning complex ideas into scalable, cloud-native solutions using AWS, Kubernetes, and robust DevSecOps practices. I lead data curation, feature engineering, and reproducible data versioning with lakeFS, while aligning experiments with STAC metadata standards and maintainable runbooks. I’m passionate about mentoring teammates, strengthening CI/CD, and collaborating with security and audits teams to ensure compliant, reliable deployments across multi-project environments.

Available to hire

Hi, I’m Cameron Wood, a Senior AI/ML Engineer with a track record of designing and delivering mission-focused AI/ML systems for research and government-adjacent projects. I specialize in PyTorch, TensorFlow, and production-ready ML pipelines, and I enjoy turning complex ideas into scalable, cloud-native solutions using AWS, Kubernetes, and robust DevSecOps practices.

I lead data curation, feature engineering, and reproducible data versioning with lakeFS, while aligning experiments with STAC metadata standards and maintainable runbooks. I’m passionate about mentoring teammates, strengthening CI/CD, and collaborating with security and audits teams to ensure compliant, reliable deployments across multi-project environments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

Bashkir

Advanced

English

Fluent

Work Experience

Senior AI/ML Engineer at Camgian

August 1, 2022 - Present

Spearheaded design and deployment of transformer-based LLMs using PyTorch and Hugging Face, reducing inference latency by 32% across four mission services. Architected end-to-end training pipelines with TensorFlow and built CNN/RNN pipelines; implemented object detection with YOLO and Faster R-CNN using Hugging Face and custom training loops. Led dataset curation, feature engineering, and reproducible data versioning with lakeFS, and adopted STAC metadata standards and runbooks for training and evaluation. Operationalized models in cloud-native environments using Docker, Kubernetes, AWS, CI/CD and DevSecOps practices, enabling faster deployment and measurable mission impact. Authored training runbooks and scaled pipelines to process multi-terabyte datasets while applying security and audit controls compatible with TS/SCI environments.

AI Engineer at University of Alabama at Birmingham Computer Forensics Lab

April 1, 2019 - August 1, 2022

Designed CNN and RNN architectures in PyTorch for forensic signal classification, improving detection accuracy from 71% to 89% across 4 datasets. Trained and fine-tuned transformer models for text reconstruction using Hugging Face, reducing downstream error rates on validation corpora by 26%. Built object detection pipelines with YOLO variants to localize forensic artifacts, delivering 82% precision on a 1,200-image test suite.

AI Engineer at UAB Computer Forensics Lab

April 1, 2019 - August 1, 2022

Designed CNN and RNN architectures in PyTorch for forensic signal classification, improving detection accuracy from 71% to 89% across four datasets. Trained and fine-tuned transformer models for text reconstruction using Hugging Face, reducing downstream error rates by 26% on validation corpora. Built object detection pipelines with YOLO variants to localize forensic artifacts, delivering 82% precision on a 1,200-image test set. Tuned preprocessing, synthetic augmentation, and feature selection to improve model generalization by 21% on cross-validation folds. Curated labeled datasets and managed metadata with PostgreSQL and SQLite, cataloging 250k+ records for traceability. Instrumented logging and basic monitoring with Prometheus-compatible exporters, enabling 24/7 visibility across 3 demo services.

Software Apprentice at Kinetic Communications

February 1, 2019 - April 1, 2019

Constructed ETL Python scripts to support client demos, reducing prototype delivery time from three weeks to one week. Prototyped Docker-based containers and basic Kubernetes manifests for lightweight services used in two demo environments. Maintained CI pipelines with Jenkins and GitHub, improving build reliability for ongoing integrations.