Mehmet Yilmaz


eBay ― Software Engineer
May 2021 - Present

  • Enhancing the Storage Management System (STMS) project to ingest 1.5+ million metrics per minute and growing. Accounting for 70+ arrays, 60+ switches, 1100+ hosts, 900+ disk groups, and 200+ clusters in 3 of eBay’s data centers.
  • Managing and deploying over 20 services across 3 regions on eBay’s Tess.IO cloud platform, ensuring high availability with failover for STMS.
  • Developing and maintaining microservices for processing hardware metrics, facilitating CRUD operations, and providing real-time data access to other internal eBay services. Utilizing JavaScript, Node.js, Express.js, Python, Flask, Mongoose, Postgres, and Sequelize to craft efficient RESTful APIs.
  • Spearheaded the migration from MongoDB to Postgres for all STMS microservices, restructuring nested documents into tables, utilizing the Sequelize ORM, and integrating middleware for a seamless transition.
  • Undertook and improved log monitoring services for Hitachi arrays and Brocade switches, ensuring prompt alerts to the storage team via email, Slack, or PagerDuty through the use of Python and Rsyslog.
  • Leveraging Docker, eBay’s container registry, and Kubernetes to streamline the containerization, deployment, and management of microservices, ensuring the scalability and high availability of STMS.
  • Engineered a pivotal backend service for eBay’s Software Defined Storage (SDS), an in-house dynamic storage provisioner, platform. This service collects and centralizes volume data (state, ownership, distribution lists, usage, etc) across eBay’s clusters, populating a database that is crucial for real-time monitoring of volume states across all of eBay’s clusters. This data was used by the SDS team to send out email notifications about volume states to users of the SDS platform. The service was built using the Kubernetes (Tess.IO) API, JavaScript, Sequelize, and mySQL.
  • Developed Restify, an Express.js backend framework, transitioning from Mongoose/MongoDB to Sequelize/Postgres. Inspired by Express-Restify-Mongoose, it specializes in GET requests, offering advanced query features like sorting, selection, limiting, distinction, and inclusion. Additionally, it includes a JSON-to-Sequelize query translator. This simplifies data querying through URL parameters and provides API endpoints for easily and efficiently querying specific STMS data by other internal eBay services. Restify served as an essential package during STMS’s transition from MongoDB to PostgreSQL.
  • Created a findOneAndUpdate() JavaScript function specifically for Postgres, inspired by Mongoose’s equivalent, and using Sequelize. The function was optimized for relational databases with efficient handling of columns, one-to-one columns, and one-to-many columns updates, while minimizing database requests by updating only the necessary fields. This function acted as an essential asset for the migration from MongoDB to Postgres in STMS.
  • Built an efficient and accurate native JavaScript package for deep comparison of object properties for both simple and complex nested key-value objects.
  • Contracted via Hitachi Vantara

Anarchy (YC W23) ― Engineering Intern (Part-Time)
Nov 2023 - Jan 2024

  • Won first place at Anarchy’s October 2023 hackathon with InsightRed, a Reddit marketing tool integrating GPT-4 and Pinecone, leading to my hire.
  • Developed an enhanced API key authentication system for Anarchy’s project, ready for future integration, featuring one-way hashing, support for multiple keys per account, and efficient validation through checksum and caching to minimize database querying.
  • Built llm-speed-benchmark, a benchmarking tool for evaluating the performance of open source LLM models; measuring tokens per second, GPU, CPU, and memory usage, along with runtime.

Colorado School of Mines ― Research Assistant
Feb 2021 - Sep 2021
Golden, CO

  • Undergraduate Research Fellow at the Human-Centered Robotics Lab, mentored by Dr. Hao Zhang.
  • Enhanced the functionality of triangular omni-wheel ground robots, called Tritons, using Python and ROS. Enabled precise movement, accurate rotation, and simultaneous control of multiple Tritons.
  • Implemented proportional feedback systems using Optitrack Cameras and ROS, enabling the Triton robots to precisely reach a specified real-world coordinate with a tolerance of +/- 0.05m within a 2m by 2m area.
  • Successfully transitioned all documentation from Google Drive and Microsoft 365 to GitLab, converting files into Markdown format, and streamlining access and collaboration within the HCR Lab.
  • Mentored a high school student in the fundamentals of programming and robotics, guiding her through the development of a ROS node for controlling the LED colors on the Triton robot.

Namasté Solar ― Intern
Sep 2017 - May 2018
Denver, CO

  • Developed an Excel tool through VBA to analyze company cash flow and employee performance.
  • Worked on designing optimal positions of solar panels on house plans through AutoCAD.

National Oceanic & Atmospheric Administration (NOAA) ― Intern
Jun 2017 - July 2017
Denver, CO

  • Worked with NOAA’s Science on a Sphere (SOSx) team.
  • Developed interactive educational content on the Apollo 11 mission for SOSx using NOAA’s Tour Builder software.

Erols Tailoring ― Customer Service
Sep 2008 - May 2018
Denver, CO

  • Provided exceptional customer service as a part of our family business, greeting, assisting, and collecting payments from customers.
  • Maintained a clean and organized workspace, managing customers’ fitted clothing and ensuring a presentable shop.
  • Responded promptly to customer inquiries and orders over the phone, providing accurate and helpful information.
  • Contributed to the success of the business during my spare time after school, on some weekends, and during some holidays.

Denver Country Club ― Tennis Court Maintenance
Jun 2015 - Aug 2015
Denver, CO

  • Cleaned indoor and outdoor tennis courts which consisted of hard, synthetic, and gravel surfaces.
  • Used the following tools for the job: golf carts, leaf blowers, tennis court squeegees, and gravel rakes.


  • Languages: Python, JavaScript, Bash Script, GoLang, Java, C++, C
  • Web Development: Node.js, Sequelize (ORM), Express.js, Postgres, MySQL, MongoDB, Mongoose, Linux, npm, Yarn, MarkDown
  • Cloud: Docker, Kubernetes, Tess.IO (eBay’s cloud platform), Vercel, Supabase
  • Tools: Git, GitHub, Zsh, Bash, VSCode, Vim, Postman, MacOS, Slack, Discord, Jira


Colorado School of Mines

  • Degree: Bachelor of Science in Computer Science
  • Date: Aug 2018 - May 2022
  • Location: Golden, CO

Denver East High School

  • Date: Aug 2014 - May 2018
  • Location: Denver, CO


Notify Cyber

  • Led end-to-end development of Notify Cyber, aggregating cybersecurity news from multiple sources into a comprehensive news feed, resulting in over 6200 visitors in the first month and averaging 30 daily visitors.
  • Engineered a Python web scraper to extract and process web articles, leveraging OpenAI’s ChatGPT API (GPT-3.5) for summarization, ensuring efficient database population.
  • Designed, deployed, and managed the project’s Postgres database hosted on the Supabase cloud service.
  • Successfully generated significant interest in the platform’s upcoming Email alert service for new vulnerabilities, amassing a waitlist of over 140 eager subscribers.
  • Minimized monthly operational costs to $3, covering the cost of the database, scraper, OpenAI API, & Vercel hosting.

Moving Pose

  • Worked on a three-person class project, implementing the paper “The Moving Pose: An Efficient 3D Kinematics Descriptor for Low-Latency Action Recognition and Detection” by Dr. Zanfir, Dr. Leordeanu, and Dr. Sminchisescu.
  • Set up the Xbox 360 Kinect sensor for real-time skeleton data acquisition using C++ and the Kinect v1.8 SDK.
  • Developed the UI by using Python, Tkinter, C++ and adapting a source code sample from the Kinect V1.8 ToolKit.

SVM On Skeleton Data

  • Developed a college project predicting human behaviors using Python, reformatting MSR Daily Activity 3D dataset to RAD and HJPD forms, and leveraging libraries like pandas, matplotlib, scipy, numpy, and libsvm.
  • Implemented a support vector machine to classify specific human activities/actions, achieving an accuracy range of 62.5% to 70.83%.
  • Demonstrated project execution with successful outcomes, showcasing accurate predictions of human behaviors within the specified accuracy range.

Simple Lane Detection

  • Developed a simple lane detection system using classical computer vision techniques, such as AOI, thresholding, Canny line detection, Hough line transform, and point clustering.
  • Implemented the project in Python, leveraging the numpy and OpenCV libraries to process video data and detect the left and right lanes from the point of view of a driving car.
  • Acknowledged limitations in the method due to video data quality, objects in the area of interest, and road conditions, while gaining valuable learning experience and a solid introduction to computer vision.


Mines Robotics Club - AgBot Team
Sep 2018 - Jan 2020
Golden, CO

  • Worked on the code for the 2019 AgBot autonomous agricultural robot, which used Python, C++, & ROS Kinetic Kame.
  • Developed a ROS publisher for detecting when the robot has reached the border of a crop field. The code was developed in Python and utilized the robot’s Lidar.