Kote Mushegiani, Developer in San Francisco, United States
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Kote Mushegiani

Verified Expert  in Engineering

Software Developer

San Francisco, United States

Toptal member since October 18, 2022

Expertise
Cloud EngineeringPythonGitHubAnsibleJenkinsLinuxAWSKubernetesGolangMachine LearningComputer VisionServerlessTerraform
Bio

Kote is a technologist and software engineer with over five years of experience with various back-end and platform systems in Python, Go, and HCL. During his career, Kote has worked with home robots, self-driving cars, and cloud-based systems ranging from real-time telematics and control to computing platforms and CI/CD pipelines.

Portfolio

Embark Trucks
Kubernetes, Go, Python, Amazon Web Services (AWS), Terraform, Ansible, Jenkins...
Toyota Research Institute
Amazon Web Services (AWS), Python, Machine Learning, Machine Vision...

Experience

  • Python - 9 years
  • APIs - 6 years
  • Amazon Web Services (AWS) - 5 years
  • Machine Learning - 4 years
  • Ansible - 4 years
  • Kubernetes - 4 years
  • Terraform - 4 years
  • Google Cloud Platform (GCP) - 2 years

Availability

Part-time

Preferred Environment

Amazon Web Services (AWS), Kubernetes, Linux, Go, Python, Terraform, DevOps, Serverless

The most amazing...

...thing I've built is a real-time system that controls semi-trailer trucks from anywhere in the world.

Work Experience

Team Lead

2019 - PRESENT
Embark Trucks
  • Led real-time vehicle telematics and operation, cloud infrastructure, and DevOps efforts until early 2021. I wrote code for these systems in Python, Go, HCL, and Bash and managed the EKS cluster and CI/CD platform.
  • Assisted in growing the original three-person team to three teams with over 15 engineers combined.
  • Built a real-time telematics solution for vehicles from scratch.
Technologies: Kubernetes, Go, Python, Amazon Web Services (AWS), Terraform, Ansible, Jenkins, GitHub, Bash, Cloud Computing, Architecture

Software Engineer

2017 - 2019
Toyota Research Institute
  • Designed, implemented, and deployed a lifelong learning framework using Amazon EC2, Amazon S3, PyTorch, and ROS.
  • Created a synthetic data generator, utilizing 2D and 3D CAD models to boost machine learning model performance.
  • Implemented a cloud-based REST API deep inference service using PyTorch, Docker, Amazon SageMaker, and AWS Lambda, unlocking the power of machine learning for low-computing devices.
  • Developed a person-following module for an autonomous mobile robot using 3D human-pose estimation in TensorFlow and deployed it on an NVIDIA Jetson TX2 embedded AI platform.
  • Built a scripting API for a guided soft target platform with an ArduRover back end for programmable collision testing of autonomous vehicles.
Technologies: Amazon Web Services (AWS), Python, Machine Learning, Machine Vision, Computer Vision, Cloud, Research, APIs, System Design, Amazon EC2, Amazon S3 (AWS S3), PyTorch, REST APIs, Docker, Amazon SageMaker, AWS Lambda, TensorFlow, Cloud Computing

Experience

Green Card to Citizenship Tracker

Developed a web app to count days and requirements toward US citizenship for green card holders. This app will help US immigrants track their travel and ensure they comply with laws to maintain US residency and apply for citizenship. The project was inspired by personally requiring this service, and I took the opportunity to learn React and expand my knowledge of the web development stack.

Education

2013 - 2017

Bachelor's Degree in Mathematics and Computer Science

Bowdoin College - Brunswick, ME, USA

Skills

Libraries/APIs

React, PyTorch, REST APIs, TensorFlow

Tools

Ansible, Jenkins, GitHub, Terraform, Amazon SageMaker

Languages

Python, Go, Bash

Platforms

Amazon Web Services (AWS), Kubernetes, Linux, Google Cloud Platform (GCP), Firebase, Amazon EC2, Docker, AWS Lambda

Paradigms

DevOps

Storage

Amazon S3 (AWS S3)

Other

Computer Science, Critical Thinking, Cloud, Complex Reasoning, Creative Problem Solving, Research, APIs, System Design, Architecture, Serverless, Machine Learning, Machine Vision, Computer Vision, Cloud Computing

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