Serenade enables developers to write code using natural speech. With Serenade, developers can use voice to add snippets, perform refactors, and automate workflows, rather than memorizing keyboard shortcuts and programming language syntax. Serenade aims to supercharge developer productivity—especially for those who may not be able to type for extended periods of time—and ultimately, empower anyone to code with voice.
Generalist Engineer San Francisco, CA, United States
Machine Learning Engineer San Francisco, CA, United States
We recently closed our seed round, and we're building out our early team—now is the opportunity to join on the ground floor.
Our co-founders were early engineers at Quora, leading teams working on developer tools and ML, and graduated from Harvard and CMU.
Serenade has a huge impact on people's lives—people with physical limitations like carpal tunnel, wrist, or back injures can be fully productive engineers through voice coding.
We're just four engineers right now, so we don't have a ton of process. We've placed a strong emphasis on code quality as a means of keeping our iteration speed high. With such a small team, we view close collaboration and direct communication as a must. We use GitHub for code reviews, and we contribute back to the open-source community as much as we can.
We have a huge breadth of technical challenges. We've built our own speech engine for translating speech to code, and we're applying the latest ML techniques to improve both accuracy and speed. We've created a generalized code manipulation platform that works by manipulating the abstract syntax trees of programs, and so we have a number of PL challenges. Finally, our product is cross-platform and plugs into several different apps, and it's a challenge to create a seamless client-side experience across all of them. All the while, we're looking to grow rapidly and keep up with scale.
Expand Serenade to new programming languages (e.g., Ruby, Go, and Rust) and editors (e.g., Sublime Text, Xcode, and IntelliJ).
Build a unified type inference platform on top of existing open-source libraries in order to enable complex refactoring operations with a single voice command.
Iterate on our best in class speech-to-code engine by applying state of the art ML techniques: building out second-phase ranking, improving our language model, and fleshing out training pipelines.
As a small team, it's critical that everyone is able to take 100% responsibility for everything they're working on—we like the mantra
nothing is someone else's problem. We value open, direct, and respectful communication and close collaboration. At our scale, we also need everyone to fill a variety of roles and be comfortable figuring out solutions to ambiguous problems. That said, we're a small team, and so everyone who joins will naturally help us define our company culture.
As a small team, we often need to collaborate closely, but ultimately what matters most to us is impact.
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