# Kyle (@kylestratis.com)

Profile: https://sifa.id/p/kylestratis.com
Headline: Founder @ Stratis Data Labs | VPEng @ Sequel Institute | AI & Machine Learning Engineering | Data Engineering | Fractional Data, AI, and AWS Consulting | Startup Advisor | Writer
Location: United States

## About

Kyle Stratis is an accomplished engineer, author, and consultant specializing in AI, data, and cloud strategies, with a proven track record of driving transformational change in technology-driven organizations. He spearheaded initiatives that revolutionized R&D efficiency, identifying process bottlenecks and implementing impactful solutions that reduced model training time from a full day to just 15 minutes, and is the author of AI Agents with MCP, published by O’Reilly Media. His innovations include an automated model training pipeline, a rapid data preprocessing feature store, and a model definition composer that empowered cross-functional teams to deliver custom solutions swiftly. Through these efforts, Kyle enabled his team to focus on innovation, resulting in faster product development and an enhanced competitive edge.

## Experience

- **Undergraduate Research Assistant at University of Florida** (2010 – 2011)
  Assisted in the execution and presentation of olfactory psychophysics research projects in the lab of David W. Smith.
- **Software Engineer at Homes.com** (2015 – 2018)
  Data Engineering
  \* Built and maintained an efficient ETL pipeline with Perl, Beanstalk, Oracle PL/SQL, Microsoft Transact-SQL, MongoDB, and Solr to process large volumes of data.
  \* Assisted in migration from Oracle databases to Microsoft's SQL Server
  \* Streamlined team testing procedures by setting up and documenting Vagrant instances of development servers
  \* Used MongoDB aggregation pipelines to improve the runtime of a process that would fail after over a week of continually running to finish in a few hours
- **Forward-Deployed AI Engineer at Tribe AI** (2024 – present)
  Working on a part-time basis on customer-facing AI projects while also having spent time building the internal Tribe AI platform and acting as a co-pilot, assisting consultant teams in using the platform effectively.
- **Writer at Real Python** (2018 – 2023)
  Write tutorials for Python programming at all levels, provide technical feedback for other writers as part of the publishing pipeline.
- **Senior Data Engineer at VIZIT** (2020 – 2022)
- **Research Infrastructure Engineer at Affectiva** (2019 – 2020)
  Built a model evaluation tool that automated a previously manual process, reducing time spent evaluating models from multiple dedicated days to a few hours of running in the background. It was also extensible, allowing the computer vision team to easily develop additional metrics for model evaluation Fixed bugs in and optimized an internal deep learning framework Helped form a team to build out a one-stop platform for the entire data lifecycle from collection through labeling, model development, and model deployment. Designed a larger system for each step of the process Assisted in the management of Affectiva’s EMPath internship program by screening candidates, advising and mentoring interns, and developing plans to grow the program by creating an intern-only conference
- **VP of Engineering at The Sequel Institute** (2025 – present)
- **Founder and Principal Consultant at Stratis Data Labs** (2024 – present)
  At Stratis Data labs, we provide services across the stack: ML Ops and platform development, AI engineering, data engineering, backend web development, and team bootstrapping.
  
  Contact us to find out how we can help your business.
- **Graduate Assistant at University of Florida** (2011 – 2013)
  Designed, executed, and presented experiments that investigated the interaction of attentional processes and the auditory system, especially at the levels of the inner ear and brainstem. Additionally assisted in teaching various classes within the Psychology Department.
- **Founder, CEO at Autem Analytics** (2017 – 2018)
  With others, founded a social analytics company to bring our chief project, Nasdanq (later, DanqExchange), the meme stock market to market. In this role, I pitched investors, ran business operations, and built and designed Nasdanq's analysis engine, which listened to social media and used a proprietary algorithm to track the engagement of memes in realtime. This allowed us to provide a stock market game where users could bet on the popularity trajectory of memes and where marketers and analysts could understand macro-level engagement patterns of any image.
- **Software Engineer at Aderant** (2014 – 2015)
  Perform bug fixes for existing applications (C#, WPF, WCF) Help create new features for existing applications Work with data and stored procedures in SQL Server 2012 (T-SQL) Perform application performance tests Work in AGILE/scrum environment
- **Senior Data Engineer at PatientsLikeMe** (2018 – 2019)
  Productionized a machine learning model on AWS as a scheduled service that emailed another team when it was time to order new blood draw kits in order to reduce waste Designed and built pipelines to ingest and transform publicly available and internal biological data into an in-house knowledge store. Evaluated and employed NLP solutions for structuring unstructured data. Evaluated tools for a department-wide knowledgebase Built and deployed machine learning models with Python, TensorFlow, and AWS Sagemaker to help answer research and business questions Employed Spotfire to create data visualization templates and administered our company's Spotfire deployment
- **Senior Machine Learning Engineer at Vizit** (2022 – 2024)
  Upgraded training server types resulting in a 36% decrease in training time and 47% hourly cost savings before taking into account decreased time spent on training each model Built new services and GraphQL endpoints on a serverless b2b SaaS backend Built a one-click model training and evaluation service that allowed for automatic and user-triggered updates of our core audience models, freeing R&D and engineering from having to manually train dozens of individual models Built a feature store database and Python library to reduce the time spent preprocessing training data by R&D Built a series of binary and multi-class image classifiers to help sort larger datasets for training more powerful models, and used those models to classify ecommerce image types Leveraged AWS’ CDK to build out our serverless data platform to support both R&D and customer success teams, with applications on the platform built in Python Created a web interface with Flask to enable teams to have graphical access to our data platform, replacing a slow 60,000 row Google sheet Built a long-term MLOps roadmap to plan future projects that will reduce time to deploy new models and enhance data and model observability Helped initiate a culture of documentation by setting up and onboarding users to Notion and building onboarding documentation and runbooks to help users efficiently run complex pipelines

## Education

- **University of Florida** — Bachelor of Science (BS) (2007 – 2011)
- **University of Florida** — Masters of Science (MS) (2011 – 2014)

## Skills

- Software Development
- Technical Writing
- Research Design
- Data Analysis
- Serverless Computing
- Neuroscience
- Artificial Neural Networks
- PyTorch
- Scientific Writing
- Keras
- MLOps
- Vector database
- SQL
- Programming
- Writing
- Statistics
- Machine Learning
- C#
- Perl
- MongoDB
- Git
- TensorFlow
- Databases
- Auditory selective attention
- Visual Intelligence
- Extract, Transform, Load (ETL)
- Science
- CDK
- Large Language Models (LLM)
- Research
- Solr
- Python (Programming Language)
- NoSQL
- Artificial Intelligence (AI)
- Experimental Design
- Python
- Teaching
- Computer Vision
- Data Engineering
- Amazon Web Services (AWS)
- Sagemaker

## Certifications

- Microsoft Certified Solutions Developer in Windows Store Apps Using C# — Microsoft
- Build a Web3 App on Ethereum with Solidity + Smart Contracts — _buildspace
- Build A Web3 App: Mint Your Own NFT Collection — _buildspace
- AI Evals For Engineers & PMs — Maven (https://maven.com/certificate/QXtWAbqm)

## Projects

- **Encryptid Gaming**
  Co-founder of early-stage blockchain gaming startup.
- **Autem Social Analytics, LLC**
  Co-founder. Unified team vision, lead architecture and implementation of data analysis engine, organized engineering team process (agile), financial planning, customer and media contact. Launched Danqex meme stock trading game (formerly known as Nasdanq).
- **Knowledge Synthesis Agent**
  As a part of the Tribe.ai LLM hackathon, I built a tool that summarizes articles, extracts any main points and arguments, and generates longer form notes expounding on those arguments. It also leverages a vector database to find similar notes in an existing knowledgebase and connects them with the new ones it cretated.
- **Evaluation of Weakly Supervised Segmentation Techniques in Microscopy**
  Evaluated traditional segmentation models such as YOLOv8 along with new models such as Meta's Segment Anything Model (SAM) against novel microscopy images, using known labels to evaluate accuracy using the Jaccard index. Used Gradio to develop a SAM demo to be presented to stakeholders.

## Publications

- Some Housekeeping Updates — kylestratis.com (https://kylestratis.com/posts/some-housekeeping-updates/index)
- A Better Practices Guide to Using Claude Code — kylestratis.com (https://kylestratis.com/posts/a-better-practices-guide-to-using-claude-code/index)
- Paying the Bills (or not) with Claude Skills — kylestratis.com (https://kylestratis.com/posts/paying-the-bills-or-not-with-claude-skills/index)
- Stop Generating MCP Servers from REST APIs! — kylestratis.com (https://kylestratis.com/posts/stop-generating-mcp-servers-from-rest-apis/index)
- The Surprising Origins of the Model Context Protocol — kylestratis.com (https://kylestratis.com/posts/the-surprising-origins-of-the-model-context-protocol/index)
- Also Announcing: AI Agents with MCP (Model Context Protocol) — kylestratis.com (https://kylestratis.com/posts/also-announcing-ai-agents-with-model-context-protocol/index)
- Announcing The Signal Path Newsletter — kylestratis.com (https://kylestratis.com/posts/announcing-the-signal-path-newsletter/index)
- A Month(ish) of Vibes with Cursor — kylestratis.com (https://kylestratis.com/posts/a-monthish-of-vibes-with-cursor/index)
- Post Training Optimizations and Formula 1 — kylestratis.com (https://kylestratis.com/posts/post-training-optimizations-and-formula-1/index)
- Tangled.sh, git collaboration on ATProtocol — kylestratis.com (https://kylestratis.com/posts/tangledsh-git-collaboration-on-atprotocol/index)
- Introducing Link Posts — kylestratis.com (https://kylestratis.com/posts/introducing-link-posts/index)
- Scalable Kubernetes Infrastructure for AI Platforms — O'Reilly Media (https://learning.oreilly.com/library/view/scalable-kubernetes-infrastructure/9798341608191/)
- Reflections On Ending 2024 as a Technology Consultant — kylestratis.com (https://kylestratis.com/posts/reflections-of-a-floating-world/index)
- Xenitia and Finding My Roots in Epirus — kylestratis.com (https://kylestratis.com/posts/xenitia-reconnecting-roots/index)
- What is Generative AI? — O'Reilly Media (https://learning.oreilly.com/library/view/what-is-generative/9781098162665/)
- Face Recognition with Python — Real Python (https://realpython.com/face-recognition-with-python/)
- Get Started with APRS with RTLSDR and Xastir on Mac — kylestratis.com (https://kylestratis.com/posts/aprs-mac-xastir/index)
- Trigger an AWS Step Function with an API Gateway REST API using CDK — kylestratis.com (https://kylestratis.com/posts/aws-api-gateway-step-func-cdk/index)
- "Yiayia" is Greater Than Two Syllables — kylestratis.com (https://kylestratis.com/posts/yiayia-greater-than/index)
- Introducing RoamLab: A Framework for Building Community Labs — kylestratis.com (https://kylestratis.com/posts/intro-roamlab/index)
- Use Sentiment Analysis With Python to Classify Movie Reviews — Real Python (https://realpython.com/sentiment-analysis-python/)
- My Information Operating System Part 3: Connecting — kylestratis.com (https://kylestratis.com/posts/my-info-os/part-3)
- My Information Operating System Part 2: Collecting — kylestratis.com (https://kylestratis.com/posts/my-info-os/part-2)
- My Information Operating System Part 1: Reading — kylestratis.com (https://kylestratis.com/posts/my-info-os/part-1)
- Combining Data in Pandas With merge(), .join(), and concat() — Real Python (https://realpython.com/pandas-merge-join-and-concat/)
- Quick Thoughts on Talks — kylestratis.com (https://kylestratis.com/posts/quick-thoughts-talks/index)
- How to Use Generators and yield in Python — Real Python (https://realpython.com/introduction-to-python-generators/)
- Supercharge Your Classes With Python super() — Real Python (https://realpython.com/python-super/)
- Splitting, Concatenating, and Joining Strings in Python — Real Python (https://realpython.com/python-string-split-concatenate-join/)
- Python Application Layouts: A Reference — Real Python (https://realpython.com/python-application-layouts/)
- 4 Techniques for Testing Python Command-Line (CLI) Apps — Real Python (https://realpython.com/python-cli-testing/)
- How a Side Project Helped Me Double My Salary — kylestratis.com (https://kylestratis.com/posts/side-project-salary/index)
- MongoDB Aggregation Pipelines to Reduce Time of Data Operations — kylestratis.com (https://kylestratis.com/posts/mongodb-agg-pipelines/index)
- Slicing and Dicing: Hash Slices in Perl — kylestratis.com (https://kylestratis.com/posts/hash-slices-perl/index)
- Hash Traversal in Perl — kylestratis.com (https://kylestratis.com/posts/hash-traversal-perl/index)
- On Imposter Syndrome — kylestratis.com (https://kylestratis.com/posts/on-imposter-syndrome/index)

## Languages

- English (native)
- Spanish (elementary)
- Greek (limited_working)

## Other profiles

- linkedin: https://www.linkedin.com/in/kylestratis