# Skyler Carlson — AI/ML Engineer

> Markdown version of https://skycarl.io/ — see also [llms.txt](https://skycarl.io/llms.txt) (site index) and the [full agent-facing profile](https://skycarl.io/llms-full.txt).

Seattle, WA — AI/ML Engineer

**I build agentic systems that ship to production.**

Skyler Carlson — Principal, Intelligence Engineering at Slalom. Ten years spanning
systems engineering, machine learning, and production agentic platforms — building
MCP servers, agentic workflows, and serverless/k8s full-stack applications on AWS,
GCP, and Azure.

- [GitHub](https://github.com/skycarl)
- [LinkedIn](https://linkedin.com/in/skyler-carlson)

At a glance:

- **50%** — LLM inference cost reduction via Bedrock batch pipelines
- **~$1M/yr** — saved automating root-cause analysis workflows with AI
- **2** — U.S. patents: voice fingerprinting & RF signal separation
- **10 yrs** — systems engineering → data science & machine learning → agentic AI

## Selected Work (2016 — present)

### Deep-research agent platform (2026 — present)

Engineering lead for a zero-to-one agentic system performing deep research and report
writing. MCP servers plus agentic data-visualization and mapping capabilities.
_MCP · Agents · Data viz & mapping_

### IOTA Hub (2025 — present)

Sole developer of a serverless platform for a citizen-science astronomy organization —
cut scientific data review from months to days for downstream consumers like NASA and
ESA. Case study: [/iota-hub/](https://skycarl.io/iota-hub/)
([markdown version](https://skycarl.io/iota-hub.md)).
_Astro/Vue · FastAPI · AWS · Terraform_

### Agentic Workflow Accelerator (2025)

Core contributor to Slalom's cloud-agnostic agentic workflow engine — built MCP server
capabilities and agent isolation functionality used across client engagements.
_Agentic workflows · MCP · Agent isolation_

### Production GenAI at Fortune 500 scale (2024 — 2026)

Matured a beta GenAI application into a production MLOps platform while halving
inference spend; separately built an event-driven personalization service that lifted
email clickthrough 85%. _Bedrock · Step Functions · MLOps_

## Experience (résumé, abridged)

### Principal, Intelligence Engineering — Slalom (2026 — present)

Engineering lead for an agentic deep-research platform for an AI infrastructure
client — hands-on from architecture through production code to delivery.

### Machine Learning Architect — Slalom (2024 — 2026)

Core contributor to the Agentic Workflow Accelerator; cut a Fortune 500 client's LLM
inference spend by 50%; led a team of three on an AI-accelerated legacy modernization
with Codex. AI SME shaping agentic solution patterns in Azure AI Foundry for
enterprise clients.

### Advanced Data Scientist — General Dynamics Mission Systems (2022 — 2024)

AI/ML Center of Excellence. Led a team of three running an enterprise RAG system with
thousands of users; ~2x improvement in radio signal collision separation with neural
networks.

### Senior Data Scientist — General Dynamics Mission Systems (2020 — 2022)

Semantic segmentation for document layout analysis; object detection on synthetic
aperture radar imagery; Python tooling for automated reporting.

### Systems Engineer → Senior Systems Engineer — General Dynamics Mission Systems (2016 — 2020)

Automated ~50% of root-cause analysis ticket workflows with AI (~$1M/yr saved); SME
for data servers and SQL operations across 30+ sites.

## Patents & Publications

- **[Voice Fingerprinting System for Detecting Hoax Emergency Reports](https://patentcenter.uspto.gov/applications/18732780)** —
  U.S. Patent 12,615,335 B2 · issued Apr 2026 · Carlson. Real-time speaker recognition
  for emergency call centers: incoming caller audio is embedded into a latent vector
  space by a neural network, and a similarity query alerts the dispatcher — while the
  call is still live — when the voice print matches known hoax callers.
- **[System and Method for Training Machine Learning Systems That Separate Radio Signals Which Overlap in Frequency and Time](https://patentcenter.uspto.gov/applications/18439904)** —
  U.S. Patent application 18/439,904 · allowed Jul 2026 · Carlson et al. A training
  pipeline that synthesizes colliding AM radio transmissions in the complex I/Q
  plane — modulation, tuning offsets, path loss, noise — and trains a neural
  separation model with SI-SNR loss to recover the individual transmissions from the
  collision.
- **[Data Generation and Separation of AM Radio Collisions with Machine Learning](https://doi.org/10.1117/12.2662948)** —
  Proc. SPIE 12529 · 2023 · Carlson, Liu, Leal, Palermo · doi:10.1117/12.2662948. No
  datasets exist for AM radio separation, so we generated one: LibriMix speech
  modulated through a synthetic RF channel. A neural network operating on I/Q data
  achieves a 98.9% higher SI-SNR than the audio-only baseline — nearly 2× cleaner
  separation at every tuning offset.
- **[StegAI: Detecting Steganography with Deep Learning](https://doi.org/10.1117/12.2662974)** —
  Proc. SPIE 12544 · 2023 · Beatty & Carlson · doi:10.1117/12.2662974. A convolutional
  network that detects least-significant-bit steganography in images at up to 96%
  accuracy — even when the hidden payload is AES-encrypted. Class-activation-map and
  entropy studies show the network keys on statistical fingerprints the payload leaves
  in the LSB plane.

## Certifications

- AWS Certified Machine Learning — Specialty · AWS · 2025 — 2028
- Certified Information Systems Security Professional (CISSP) · (ISC)² · 2020 — 2029
- AWS Certified Solutions Architect — Associate · AWS · 2025 — 2028
- Google Associate Cloud Engineer · Google Cloud · 2025 — 2028
- SnowPro Specialty: GenAI · Snowflake · 2025 — 2027
- SnowPro Core · Snowflake · 2025 — 2027

## About

I'm passionate about building AI, ML, and automation-forward solutions to salient
business problems. I'm a big-picture thinker who connects AI/ML to tangible business
impact, then owns the whole stack to get it shipped — architecture, infrastructure,
application code. I develop with Claude Code daily and thrive at the intersection of
people, process, and automation.

Outside of work, I love to spend time outdoors! I spent six years as a mountain rescue
technician in southern Arizona — 130+ missions with the Southern Arizona Rescue
Association. These days I enjoy running (roads and trail) and exploring the Washington
mountains. I also enjoy building software in my free time, tinkering with home
automation, and gardening.

## Education

- **M.S., Data Science** — Johns Hopkins University (2018 — 2021). Machine learning
  and advanced machine learning, computational statistics, statistical models and
  regression, algorithms for data science, and stochastic differential equations.
- **B.S., Systems Engineering** — The University of Arizona (2013 — 2016). Minor in
  Mathematics. Dean's List with Distinction; senior design team leader for an
  autonomous-vehicle testbed for GNC algorithm testing.

## Contact

Open to interesting problems in agentic systems, applied ML, and the occasional
astronomy side quest. The fastest way to reach me: **sky@skycarl.io**