Description

JusticeText is a pre-seed technology startup focused on driving criminal justice reform via technological solutions. We work with public defense agencies across the country to develop video evidence management software that strengthens their ability to advocate for everyday citizens. Racial and economic justice is at the core of our company mission, and we believe technological innovation has an important role to play in this movement. 

Our justice system is being inundated by the 3 trillion hours of video which is captured everyday worldwide from surveillance cameras, body-worn cameras, dashboard cameras, witness interrogations, and more. While video evidence is involved in over 80 percent of criminal cases, this crucial data can easily go overlooked without the tools necessary to analyze it. This challenge is even further exacerbated within the public defense system, which is tasked with representing low-income criminal defendants across the US.

We are building an AI-powered video evidence management platform that enables public defense attorneys to more effectively identify relevant insights from audiovisual evidence. By providing value for public defense attorneys through time saved, we aim to ensure fairer outcomes for those most vulnerable. 

JusticeText was co-founded by Devshi Mehrotra and Leslie Jones-Dove in January 2019 while they were both computer science students at the University of Chicago. The first iteration of the product was built in direct collaboration with the Cook County Public Defender's Office in Chicago. The company received initial funding from David Axelrod, former Senior Advisor to President Obama. Since then, JusticeText has rapidly expanded and held paid pilot programs with offices in California, Minnesota, Texas, Louisiana, and Nevada. 

We were accepted as part of the Duke Law Tech Lab and Envision Accelerator for the summer of 2020 and are eager to onboard additional engineering talent onto our team as we continue to grow in the upcoming months.

Learn more about us here:

As a full-stack engineer at JusticeText you will be responsible for implementing the user facing features that will increase the usability and helpfulness of the platform to public defenders. Most immediately, you will help improve the overall user experience of our editor as we migrate our backend to better support the machine learning capabilities of our platform. We additionally host regular feedback sessions with public defenders where we get to find out what is working and what isn’t in our platform. These sessions will be a unique opportunity to engage directly with key stakeholders in our criminal justice system and translate their feedback into defining a product roadmap for JusticeText.

As an early engineer, you will also help shape our engineering process to better maintain engineering excellence and speed. The faster we can get high quality, valuable features out the door, the quicker public defenders can help get people out of jail and give them the second chance that we all sometimes need and deserve.

In the event that we are able to meet our fundraising goals, there will be the opportunity to convert this position into a full-time role.

Skills and responsibilities

  • Design and development tested UI features that tie in data from backend REST api endpoints
  • Implement UI/UX changes from UI mocks
  • Understand the overall JusticeText platform architecture and how that informs the frontend
  • Reducing technical debt through good code hygiene and utilizing best coding practices

Details

  • Location:
    San Francisco
    ,
    CA
  • This job is remote friendly.
  • Deadline:
    2020-08-14

Qualifications

Minimum qualifications

  • Kind, compassionate, and has a passion for social justice
  • Self-motivated and eager to be a thought partner is the development of the JusticeText product roadmap
  • Experience working with our tech stack, specifically React, Redux, Node, and JavaScript or TypeScript
  • Familiarity with broader web concepts (i.e. CORS, REST requests, web security)
  • Knowledge of design patterns and when best to use them

Preferred qualifications

  • Python and machine learning experience in natural language processing (NLP) 
  • Familiarity with Amazon Web Service and working in the AWS console