Facet is building artist-centric applications that bridge the gap between tool and assistant, freeing artists to explore new ideas and produce better work. While media becomes increasingly personalized and topical, the process of creating art remains frustratingly manual. We use machine intelligence to amplify human creativity, allowing artists, designers, and creatives of every stripe to realize their visions simply and easily.
We have just launched our first product, a web-based ML-powered image editor, into private beta, and we're expanding our founding team in San Francisco. Facet is backed by Slow Ventures, Basis Set Ventures, South Park Commons, and a diverse group of designers, product thinkers, as well as AI engineers from Google Brain and Salesforce.
Software Engineer (Backend) San Francisco, CA, United States or Remote
Software Engineer (Frontend) San Francisco, CA, United States or Remote
Why join us?
AI for creative tools is something we at Facet believe very deeply in—we're truly at the cusp of a renaissance in UX design. Tech at the intersection of visual perception and synthesis is already creating to more powerful tools for professionals as well as new forms of media and art (e.g., Cindy Sherman's snapchat-filter pieces). More tellingly, it is creating new ethical challenges, e.g. AI coupled with the rendering and special effects pipelines of Pixar or ILM has deep implications on what constitutes evidence in criminal cases, and has severe potential for abuse for systems like DeepFakes, or that, e.g., can synthesize photo-realistic video of Obama synced up to any audio clip.
Facet has the potential to become a huge independent powerhouse, making creative work easier and more accessible for folks of all stripes. We're the right team for this problem, we're highly technical, and we are backed by AI and product experts from Google Brain, Salesforce Metamind and FAIR. Joe founded two successful companies prior to Facet: Metamarkets was acquired by Snap last year and Premise has expanded to provide basic income and data services to underserved communities in over 30 different countries. Matt has deep expertise in computer graphics and machine learning, and previously led the engineering team at Operator.
As an startup, Facet is high risk, and to be transparent, there is no way we can guarantee our success, but we're well positioned to be smart about it. That said, you’re joining a company at its earliest stage as a member of the founding team, and you’ll have a significant equity stake and influence on our product and culture. We’re going to make mistakes, we’re going to write and rewrite a ton of code, and we’re going to struggle with product direction and market development. We’re being upfront because above all else we value honest communication and collaboration. There is no other way to successfully navigate a seed stage business. By working together, we can go farther, faster, and accomplish more than any of us could by ourselves.
Engineering at Facet
The team focuses on four core areas: frontend engineering, backend engineering, image rendering, and ML/AI. We're still at a size where most of our engineers work on more than one of these areas.
Most projects are executed by groups of 1-3 engineers. Typically, each engineer owns at least one project.
We have a weekly sprint cadence, with daily standups in Slack and issue tracking / discussion on Github. All commits require a code review / second set of eyes. Commits to master run automatically against a testing suite and are deployed continuously to our dev environment.
We run a quarterly lightweight all-team planning process to brainstorm, scope, and prioritize new projects. This isn't the only time that we introduce new project ideas, and we do regularly reassess these plans as the quarter progresses, but this process still helps ensure that we continuously work towards our longer-term goals.
UI architecture and design: a full-featured image editor like Facet is a complex application with many different interaction modes, and a large amount of state. Managing this complexity requires careful thinking about architecture, performance, and design practices.
Scalable backend rendering: we offer image rendering APIs that require us to be capable of generating many high-resolution renders from our image processing pipeline, each of which may depend on results from several of our AI-based image processing services.
Real-time browser-based image processing: Performing complex editing operations on millions of pixels in real time isn’t easy. We need to use GPU acceleration, careful memory management, and extensive caching — and we’re looking at any web technology that could give us a boost. We use WebGL extensively, and we’re beginning to use WebAssembly to make sure photo editing always feels fluid.
Interactive AI models: Many AI models won’t run in the browser, but we can’t get real-time interactivity by running solely on the server. We are constantly trying to figure out new ways to use server-side precomputation with client-side postprocessing in order to make AI-generated results available interactively, to enable fast creative iteration.
Facet currently allows users to select AI-recognized objects from a single photo. Allow users to composite multiple photographs into a single frame, and select objects from all of them. This requires new UI for arranging images, new selection logic for combining selections from multiple images, and extensions to Facet's selection description for disambiguating single vs. multiple image selections (did you want to select all cars from any image, or just the cars in a single image?).
Facet's image rendering API currently supports applying a set of user-created image edits to new photographs submitted via a REST endpoint. Extend the rendering API to allow clients to request variations of those edits as well - for example, a range of exposure adjustments. This requires extending our rendering and caching logic, as well as designing a simple and extensible method for specifying modifications to an image.
Facet does a pretty good job with recognizing objects in an image. But what if the thing you want to select isn't really an object? For example: a shadow, a wall, the sky. Find ways to combine parts of existing AI-based image segmentation techniques with object selection and matting methods from traditional computer graphics to allow for easy interactive selection of meaningful non-object parts of an image.
Working at Facet
Consensus goals, independent execution. We value collaboration on goal setting and technical/company direction while giving individuals latitude and ownership over how these goals are achieved.
Decathlon not a sprint. Creative AI is a rapidly blooming space, so we need to move quickly to build our product and grow our market. We all juggle multiple roles and we’re in it for the long haul. At the same time, we need to build a stable foundation for our future work, and ensure that we are building thoughtfully, creating a product that makes the world better, and only breaking things if we’re pretty sure we can fix them again. Furthermore, we understand downtime is important. We don’t have an explicit vacation policy, but unlike other startups we expect you to gauge your level of stress and take one when you need it.
Creative+Technical. Facet is about making technology a partner in the creative process. We enjoy product design, engineering, and research—but also photography, music, art, and cooking.
Diverse ideas. We’re solving a completely new problem and need a diverse set of viewpoints and voices to fully understand its scope and extent. We’re building a company and culture that can responsibly and respectfully integrate a plurality of voices.
Tea and baked goods. We’re really into tea and baking & think these are good things. You might disagree with us (cf. “diverse ideas”) but jfyi.
Work from Home
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