About Me
Machine Learning Engineer and Full-Stack Developer passionate about building intelligent applications that solve real-world problems.
My Story
My journey into machine learning wasn't a traditional path, and that's become my greatest advantage. After building a career in analytical roles, I faced health challenges that gave me an opportunity to step back and reassess where I could make the most meaningful impact.
During this period of recovery, I gained a valuable new perspective. I recognized that the most significant barrier to successful AI implementation wasn't technical expertise but understanding how technology integrates with and transforms business processes. This insight inspired my transition into machine learning with a focus on systems thinking.
I've dedicated myself to building both the technical skills and the business process understanding needed to bridge this gap. Rather than seeing machine learning solely through the lens of algorithms and models, I approach it as a transformative tool that must be thoughtfully integrated into existing systems.
Today, I combine technical machine learning expertise with a systems perspective to build solutions that don't just perform well in isolation but create lasting value through effective implementation. I'm particularly focused on making advanced technology accessible through clear documentation and thoughtful integration with business processes.
Skills & Expertise
Machine Learning
Neural networks, transformers, computer vision, NLP, model deployment, and MLOps.
Software Development
Full-stack development, API design, cloud architecture, and system integration.
Data Science
Data analysis, visualization, ETL pipelines, statistical modeling, and feature engineering.
Systems Thinking
Integrating AI with business processes, change management, and holistic implementation strategies.
Professional Journey
Machine Learning Engineering Focus
2023 - Present
Building machine learning models with a focus on systems integration and business process transformation. Developing expertise in combining technical excellence with practical implementation.
Career Transition & Skill Development
2021 - 2023
During a period of health recovery, I reassessed my career direction and focused on developing machine learning skills. This perspective shift highlighted the importance of systems thinking in effective AI implementation.
Program Management
2018 - 2021
Led cross-functional teams in implementing analytics solutions and business intelligence systems. Developed expertise in translating data insights into actionable strategies for business units.
Military Leadership
2011 - 2018
Served in leadership roles developing analytical frameworks for operational assessment. Built skills in strategic planning, team leadership, and complex problem-solving.
Systems Thinking in Machine Learning
I believe the AI skills gap isn't primarily about technical expertise—it's about systems thinking. While many ML practitioners focus solely on model performance, I evaluate solutions through the lens of how they transform entire business processes.
When implementing AI, I consider the ripple effects across departments, workflows, and stakeholders. This perspective ensures that machine learning solutions don't just perform well in isolation but create lasting value through thoughtful integration with existing systems.
Process Transformation
Redesigning entire business processes to leverage AI capabilities, not just adding models to existing workflows.
Human-Centered Implementation
Considering the human elements of AI adoption, including training needs, communication strategies, and role evolutions.
Business Alignment
Ensuring ML initiatives align with strategic business outcomes rather than merely optimizing technical metrics.
Let's Work Together
I'm always open to discussing new projects, creative ideas, or opportunities to be part of your vision.