From Military Radar to Machine Learning: A Career Transition Story

From Military Radar to Machine Learning: A Career Transition Story

Twenty years in the Coast Guard taught me to see patterns in chaos. Whether tracking vessels on radar screens or troubleshooting complex military systems, the core skill was always the same: extract meaningful signals from noisy data.

I just never expected that skill would lead me to patent-pending acoustic algorithms.

The Radar Years

My Coast Guard career began in 2000 as an Electronics Technician, working with military radar systems like the SPS-73, SPS-50, and SPS-64. These weren’t just machines to maintain - they were my introduction to the art of signal processing.

Radar taught me fundamental concepts that would prove invaluable decades later:

  • Signal vs. Noise: Distinguishing real targets from interference
  • Range Estimation: Using signal strength to calculate distance
  • Pattern Recognition: Identifying aircraft, ships, and weather patterns
  • System Reliability: Building robust detection systems

By 2011, I was Chief Electronics Technician on a polar icebreaker, leading teams of 11 technicians. By 2015, I was managing 55 technicians across the largest Coast Guard area of responsibility in the nation.

The Amazon Scale

Transitioning from military service to Amazon in 2019 was like jumping from a speedboat to a cargo ship - everything was bigger, faster, and more complex. As a System Development Engineer, I found myself managing 23,000 EC2 instances serving millions of transactions per second.

The scale was overwhelming, but the principles remained the same:

  • Pattern Recognition: Identifying performance bottlenecks in massive systems
  • Signal Processing: Extracting meaningful metrics from terabytes of logs
  • System Reliability: Keeping critical infrastructure running during peak events
  • Team Leadership: Coordinating complex operations under pressure

Amazon taught me that the skills I’d developed in the military - seeing patterns, managing complexity, building reliable systems - were exactly what modern technology companies needed.

The Academic Bridge

Starting Computer Science studies at Evergreen State College in 2023 gave me the theoretical foundation to understand what I’d been doing intuitively for years. Concepts like algorithms, data structures, and computational complexity finally had names.

As a Teaching Assistant, I found myself explaining code to students, helping them debug programs, and facilitating demo days. The teaching role reinforced something important: the best way to truly understand a system is to build it yourself.

The Consulting Success

My recent work with TEKSystems, migrating 20+ pipelines for Amazon (250% above quota), proved that military-trained problem-solving skills translate directly to high-performance consulting. The ability to:

  • Analyze complex systems quickly
  • Build automation tools to eliminate manual work
  • Document processes clearly (including that first-of-its-kind COE)
  • Deliver results under tight deadlines

These weren’t new skills - they were military skills applied to civilian problems.

The Innovation Breakthrough

SkySentinel represents the convergence of everything I’ve learned:

  • Military radar experience: Understanding detection systems and signal processing
  • Amazon scale expertise: Building robust, cloud-native architectures
  • Academic foundation: Applying computer science principles systematically
  • Consulting mindset: Delivering practical solutions that work

The acoustic aircraft detection system uses the same fundamental concepts I learned on Coast Guard radar systems, just applied to sound instead of radio waves.

The Pattern Recognition

Looking back, there’s a clear pattern in my career transitions:

Military (2000-2019): Learn to see patterns in complex systems Amazon (2019-2023): Apply pattern recognition at massive scale Academia (2023-present): Understand the theory behind the practice Consulting (2024): Prove the skills transfer to any domain Innovation (2024-present): Combine everything into novel solutions

Lessons for Other Transitioning Veterans

The transition from military to tech isn’t about learning completely new skills - it’s about translating the skills you already have:

  1. Systems Thinking: Military teaches you to see the big picture
  2. Reliability Focus: Mission-critical systems can’t fail
  3. Team Leadership: Complex operations require coordination
  4. Problem Solving: When things break, you fix them quickly
  5. Continuous Learning: Technology evolves, so must you

The Unexpected Connection

The most surprising discovery? My Coast Guard radar experience directly informed my acoustic detection algorithms. Both involve:

  • Detecting objects at a distance using wave propagation
  • Distinguishing targets from background noise
  • Estimating range using signal strength
  • Classifying targets based on signature patterns

Twenty years of radar experience didn’t become obsolete - it became the foundation for innovation in a completely different domain.

The Future

Today, I’m a Computer Science student, teaching assistant, consultant, and patent-pending innovator. The military gave me the foundation, Amazon gave me the scale, academia gave me the theory, and consulting proved the transferability.

SkySentinel is just the beginning. When you understand how to extract signals from noise - whether it’s radar, logs, or acoustic data - the applications are limitless.

For veterans considering a transition to tech: your military experience isn’t something to overcome - it’s your competitive advantage. The skills that made you successful in uniform are exactly what the technology industry needs.