Matter is building the future of reading.

We're a small, productive team that obsesses about craft, speed, and pushing technical boundaries in service of building the best reading experience imaginable.

We've raised $9M while in private beta from GV, Y Combinator, and many stellar angels, and we just launched to public beta.

You might be a fit if you:

• Are an experienced generalist who writes high-quality code.
• Can own large pieces of work and solve whatever problems come your way.
• Have designed APIs and built backend services for complex, consumer-grade products.
• Are comfortable with Python/Django/SQL/AWS. Languages can be learned, but because we're small and will be counting on you to make big contributions quickly, familiarity with our stack is helpful. ML experience a plus.
• Operate well in an early-stage environment where there's more change and less structure compared to a more mature company.
• Are highly collaborative and an excellent communicator.

Some tech you'll help build:

• Article and PDF parsers that use a combination of techniques from heuristic frameworks to NLP to computer vision
• Data ingestion pipelines that consolidate content from disparate sources, including RSS, save-extensions, newsletters, and Twitter
• Scrapers that ingest content produced by specific individuals wherever it occurs on the internet
• Data synchronization engine that powers offline interactivity across multiple clients

Our Stack

• Django, Postgres, Redis, Celery in the backend
• Swift iOS app with Realm for local datastore
• React for internal tooling
• Runs entirely on AWS
• Comfortable dev environment using Git, Docker, automated tests, and continuous deployment
• GitHub, Slack, Notion, Figma, Linear

Some tech you'll help build

• Article and PDF parsers that use a combination of techniques (eg. NLP, computer vision) to achieve best-in-class performance
• Data ingestion pipelines that consolidate content from disparate sources, including RSS, save-extensions, newsletters, and Twitter
• Scrapers that find and ingest articles by specific writers wherever they occur on the internet
• Audio-to-text transcribers that map audio files to editable transcripts (similar to Descript)
• Subscriptions layer that lets users frictionlessly manage their paid subscriptions to 3rd party publishers
• Integrations with Readwise, Roam, Notion, and other services
• A powerful and simple API
• Models that profile the "DNA" of articles (eg. quality and complexity of writing, topics, political valence, and so on)
• Content recommendation systems that take into account behavioral data, social signals, and other factors

Our Stack

• Django, Postgres, Redis, Celery in the backend
• Swift iOS app with Realm for local datastore
• React for internal tooling
• Comfortable dev environment using Git, Docker, automated tests, and continuous deployment
• Run entirely on AWS
• GitHub, Slack, Notion, Figma, Linear