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JORDAN M. WITTE

wittejm@gmail.com

Portland, OR

TECHNICAL SKILLS

Full-Stack Development

  • Software Engineering, 6 years (Java 2 years, React/Python 2 years, React/Node 2 years)
  • Python, 7 years (including machine learning research tools)
  • Web API with Flask; JVM + SOAP; GraphQL + Apollo
  • Frontend engineering with JS/Typescript, React/Redux
  • Collaborative development with source control and review, Git Test-driven development with Jest, PyTest, JUnit
  • Full-stack architecture and deployment with Nginx, Docker CI/CD with GitHub Actions, TravisCI

Data Engineering

  • Relational databases with SQL, 4 years
  • Data integration with middleware and backend services using Python/Java libraries
  • Data acquisition, exploration, and modeling
  • Python science packages Numpy, Scikit-Learn, Matplotlib
  • Machine learning techniques for visual object detection and structured learning
  • Fluency with scientific research papers in AI and machine learning

CURRENT WORK

Code for PDX at Portland, OR (volunteer)

Feb 2023-Present

Software Engineer

CONTACT: Hugh Harker, Organizer

PRIOR WORK EXPERIENCE

2021-2023: Ameelio, Inc. (remote)

Software Engineer

  • Full stack: Typescript/React/Node, GraphQL, Postgres, Docker

CONTACT: Lance Ivy, Principal Engineer

2019-2021: Code for PDX at Portland, OR (volunteer)

recordsponge.com

Full-stack Developer, Project Manager

  • Full stack: Python, Flask, JS/Typescript, React, Redux, Postgres, Docker
  • Product development with users and domain research (criminal law, public health)
  • Collaborative development, organizing volunteers, new contributor on-boarding

CONTACT: Michael Zhang, JD (www.qiu-qiulaw.com)

2021: PAST LIVES, LLC at Portland, OR

Data Engineer

  • Developed data models for core business operations
  • Designed and deployed core business workflows using Airtable

CONTACT: Brandon Morlock, Founder

2017: DIGIMARC CORPORATION at Beaverton, OR

Machine Learning Researcher

  • Developed high-speed visual pattern recognition algorithms
  • Neural network model tuning and evaluation
  • Model implementations in Keras/TensorFlow

CONTACT: Tony Rodriquez, CTO

2016: LOS ALAMOS NATIONAL LABORATORY at Los Alamos, NM

Student Graduate Researcher

  • Built depth-aware sparse neural networks for visual object detection and depth prediction
  • Experiments in PetaVision: an open-source, large-scale sparse neural net framework
  • Contributed experimental results and open source analysis tools in Python

CONTACT: Garrett Kenyon, LANL Staff Scientist

2015: PERCEPTRONICS SOLUTIONS at Portland, OR

Data Science Researcher

  • Developed data mining tools for political and marketing campaign analysis
  • Social network modeling using graph structures and algorithms in Java
  • Live data collection using 3rd-party Java APIs

CONTACT: Tim Chabuk, Director, Intelligent Information Systems

2012-2014: CITIGROUP Inc. at Buffalo, NY

Java Developer

  • Primary developer for multiple projects, including project spec and design
  • Multi-process job scheduling using thread libraries and inter-process communication
  • Integration with UX teams and existing business workflows
  • In-team QA with Unit Testing (JUnit)
  • Oracle SQL with Java API

CONTACT: Michael Cooney, Senior Project Manager

GRADUATE STUDENT RESEARCH (2014-2019)

  • Developed scene recognition methods combining CNN architectures and structured reasoning
  • Applied statistical models for semantic image interpretation
  • Teaching Assistantships in Theory of Computation, Machine Learning, Operating Systems, and others

ADVISOR: Melanie Mitchell, Professor at Portland State University

RESEARCH PUBLICATIONS

  • Quinn, M. H., Conser, E., Witte, J. M., and Mitchell, M. (2018). Semantic image retrieval via active grounding of visual situations. In Proceedings of the 12th International Conference on Semantic Computing. IEEE.
  • Rhodes, A. D., Witte, J., Mitchell, M., and Jedynak, B. (2017). Bayesian optimization for refining object proposals. In Proceedings of the 7th International Conference on Image Processing Theory, Tools, and Applications (IPTA 2017). IEEE.