Who I am

Jua Docs is a technical writing studio that brings clarity to complex systems.
Founded by Jameelah Mercer, Jua Docs helps developer tool companies, open source projects, and startups scale their docs with developer-first clarity.

With experience in applied mathematics, machine learning, and high-performance computing, we specialize in writing documentation that engineers trust and users can follow.

Whether you're launching an API, rewriting a CLI guide, or improving onboarding, we're here to help your documentation work as hard as your code.

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Jameelah N. Mercer

Technical Writer | Developer Documentation | DevOps & ML Systems
github.com/MeelahMe

Summary

Detail-oriented technical writer with experience creating developer-focused documentation for platforms, APIs, CLIs, and machine learning systems. Proven ability to translate complex concepts into clear, actionable content using docs-as-code workflows. Collaborates cross-functionally to deliver high-impact docs that enhance user experience and support product adoption.

Skills

Technical Writing:
Proposals · Technical Documentation · Blogs · Technical Reports · APIs · User Guides · Data Analysis Reports · Diagrams & Illustrations

Languages & Tools:
Python · Java · MATLAB · Markdown · Bash · Linux · Git · TensorFlow · Docker · Kubernetes · Prometheus · Grafana · SQL · Hugo · YAML

Professional Experience

InfluxData

Technical Writer Intern
December 2024 – Present | Remote

  • Authored and maintained developer docs for InfluxDB’s APIs, CLIs, and client libraries across multiple languages.
  • Developed technical blog posts and tutorials that improved developer engagement and platform adoption.
  • Shipped content using a docs-as-code workflow with Hugo, Markdown, YAML, Redoc, Git, and Bash.
  • Collaborated with engineers and product managers to ensure accuracy and completeness.
  • Tested documentation in developer environments using Docker, Python, JavaScript, Bash, and SQL.

Lawrence Berkeley National Laboratory – NERSC

DevOps Engineer Intern
2019 – 2021 | Berkeley, CA

  • Designed technical documentation for HPC systems, including Docker and Kubernetes Pods.
  • Documented monitoring setups using Prometheus and Grafana.
  • Created detailed user manuals for infrastructure monitoring and data reporting systems.
  • Used GitHub for version control and collaborated with engineers to document release processes.

Machine Learning Experience

Circuit Launch

Machine Learning Enginner Intern
Summer 2022 | Oakland, CA

  • Built a miniature autonomous car and collected training data using computer vision.
  • Trained a convolutional neural network using Keras, Python, and TensorFlow.
  • Implemented a deep learning autopilot using behavioral cloning (imitation learning).
  • Wrote and formatted technical documentation for ML models and software systems using Markdown and GitHub.

Extracurricular & Project Experience

High Performance Computing Club

Member
2019 – 2020 | Berkeley, CA

  • Competed at the SC18 International Conference for High-Performance Computing, Networking, Storage, and Analysis.
  • Built and maintained a miniature supercomputing cluster using Git, Linux, Python, and Bash.
  • Configured Horovod for distributed training with TensorFlow, Jupyter Notebook, and Matplotlib.
  • Created documentation for system architecture and deep learning workflows.

Deep Learning School for Science (DSL4SCI)

Participant
2018 – 2019 | Berkeley, CA

  • Collaborated with researchers and engineers while attending lectures and tutorials on advanced deep learning methods and HPC systems.
  • Facilitated discussions on how modern learning algorithms can support scientific research.

Additional Research Experience

University of California Berkeley, Berkeley Sensor and Actuator Center

Visiting Researcher
2017 – 2019 | Berkeley, CA

  • Executed hardware tests with oscilloscopes, acquisition units, DMMs, and analyzers, applying analog and digital principles.
  • Analyzed novel sensors to determine the instantaneous direction of power flow in commercial systems with intermittent sources.
  • Designed schematics for circuit analysis and performed system-level evaluations.
  • Assembled and tested magnetic field sensors using microcontrollers.
  • Conducted data and research analysis using MATLAB and AutoCAD.

Lawrence Berkeley National Laboratory

Research Assistant
2015 – 2017 | Berkeley, CA

  • Analyzed indoor air quality to characterize microfluidic sensors for airborne particles.
  • Assembled and tested sensor components for performance analysis.
  • Conducted data analysis of particulate matter using Excel.
  • Prepared experimental results using Google Charts, PowerPoint, and Excel.

Education

Associate of Science – Mathematics

Berkeley City College · May 2021

Bachelors Of Science - Applied and Computational Mathematics

San Jose State University · Expected December 2025

Contact

Have a project in mind or just exploring what’s possible? Fill out a few quick details and I’ll follow up shortly.

And if you don’t see exactly what you need—no problem. I offer custom solutions tailored to your product, team, and goals.

At Jua Docs, every project starts with a thoughtful conversation. Let’s talk.