Build intelligence that helps people to focus and bring new ideas to life

Journal is a new productivity platform for people and teams. We make it simple for everyone to find, remember, and share information from anywhere. Our vision is to build a "space” that helps people discover and save ideas, collaborate on projects, and avoid distractions. If you’re excited by the opportunity to help people focus and bring new ideas to life, join us at Journal!
 
Journal is backed by Khosla Ventures, Slack Fund, Social Capital, Abstract Ventures, and Product Co-op.
 
Journal’s infrastructure is built on top of AWS and Kubernetes. Our clients include Lumos (Desktop app), Fawkes (Web app), Pensive (Mobile app) and Hedwig (Chrome extension), all built with React and React Native. They communicate with our Java-based backend service Imperio using GraphQL, which in turn uses GRPC to communicate with various backend microservices which front our relational databases and search infrastructure. Backend scheduled tasks to fetch information are scheduled on a Kubernetes cluster and use SQS/Redis to coordinate work. Our primary databases are MySQL (RDS), Elasticsearch and a distributed vector database created in-house to power our state-of-the art conceptual search. 
 
We’re looking for people with a strong background (or interest!) in machine learning. We’d love to hear from you whether you’re a machine learning engineer, or whether you’ve just learned you might like working with machine learning. Bonus points if you picked up on our naming scheme!
 

You will work be:

  • Designing, building and maintaining the search infrastructure for Journal
  • Designing, building and maintaining a distributed vector database, powering the state-of-the-art Journal search system
  • Leveraging user’s information to provide intelligence and aid them in their day-to-day tasks
  • Creating recommendation systems to help users find the right information without actively looking for it
 

You’ll do great in this role if you:

  • Think about creative ways in which software and machine learning can automate and aid tasks for people
  • Thrive in uncertainty and enjoy creating direction where it’s never existed before
  • Are deeply knowledgable about how to manipulate data to perform analysis, including querying data, defining metrics, or slicing and dicing data to evaluate a hypothesis
  • Have an understanding of data persistence (relational, key/value, document, columnar, graph)
  • Hold yourself and others to a high bar when working with production
  • Are able to write high quality code in a programming language (e.g. Python, Java, Go, Clojure, Haskell)
 
It’s not expected that any single candidate would have expertise across all of these areas. For instance, you might still be a great fit if you are really focused on creating great models but don’t come in with as much databases knowledge.
 

You’ll work alongside teammates with complementary skillsets:

Samiur Rahman (Co-founder, CEO)
Samiur builds Journal’s conceptual search and machine learning data extraction engine and keeps the company moving in the right direction. Outside the office Samiur is on a quest to make the perfect brisket.
 
 
Mark Philpot (Head of Engineering)
Mark builds Journal’s apps and our GraphQL API. Outside the office Mark perfects his photography skills, shooting portraits of his two adorable kids.
 
  
Avi Eisenberger (Co-founder, Product)
Avi runs product and designs everything for Journal. Outside the office Avi is either in the middle of nowhere surfing, skiing, and biking, or he's taking his sweet golden retriever, Benji, for a long walk.
 
 
Sam DeBrule (Co-founder, Marketing)
Sam writes our ‘Machine Learnings’ newsletter and grows Journal’s user base. Outside the office he is face-first in a book or running the tread off his sneakers.
 

Why we’re building Journal

At Journal, our mission is to help people focus and bring new ideas to life. Much of our personal and professional lives run on apps. Yet these tools create boundaries between our activities, require constant checking, and have enabled a culture of interruptions. Journal will give individuals and groups a focused “space” to find, remember, and share all the information they need to have fun and do good work.

How we work together at Journal

We value communicating new ideas with first drafts, using diverse perspectives to guide decisions, and trusting each other’s potential to solve big problems.
 
Journal is an equal opportunity employer. We are open to all types of backgrounds and we value a diverse team.

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