Rosebud.ai is building the synthetic media platform for web3. We are helping creators make composable assets for web3 world building.
We're the team that built Tokkingheads (2 million IOS downloads, all organic) that allows any portrait/photo/face to be animated in seconds with no skill. Creators use Tokkingheads to make memes, deepfake parodies, NFTs. We’re a team of PhD researchers, creatives and engineers backed by Y Combinator with our seed led by Vinod Khosla at Khosla Ventures with participation from Balaji Srinivasan **(Former CTO Coinbase and A16Z GP), Ilya Sutskever (cofounder/chief scientist Open AI), Kevin Lin (cofounder COO Twitch), Holly Liu Co-founder Kaba, Kun Gao (cofounder, CEO Crunchyroll), Linda Xie Founder Scalar Capital, Jon Snoddy SVP @ Walt Disney Imagineering, Jeff Dean SVP Google Research, Adam D'Angelo CEO Quora, and Lily Liu. cofounder http://earn.com.
Rosebud.ai building generative AI workflows to accelerate game development and creative. We want to empower indie devs to build games at the speed of thought.
We're the team that built Tokkingheads (2 million IOS downloads, all organic) that allows any portrait/photo/face to be animated in seconds with no skill. And Synth (https://www.synth.run), a simple mobile app that allows users to create images based on Stable Diffusion. We’re a team of PhD researchers, creatives and engineers backed by Y Combinator with our seed led by Vinod Khosla at Khosla Ventures with participation from Andrej Karpathy, Balaji Srinivasan **(Former CTO Coinbase and A16Z GP), Ilya Sutskever (cofounder/chief scientist Open AI), Kevin Lin (cofounder COO Twitch), Holly Liu Co-founder Kaba, Jon Snoddy SVP @ Walt Disney Imagineering, Jeff Dean SVP Google Research and Adam D'Angelo CEO Quora.
🚀 Join a Rocket Ship!
🚀 Ship products that delight millions of users while having direct product impact on a small team (2 million downloads in over 180+ countries).
🚀 Do cutting edge ML and full stack work
🚀 Fully remote--live anywhere!
🚀 Work with a passionate, low ego, world class team!
Our team is still quite small (<10), so you’ll have massive impact on the trajectory of the business from Day One.
You fit well if you have great experience in modern natural language processing dl based methods, if you can take some idea or business task, find good open source or implement simple methods to create prototype, package all of this for demo and always have ideas on how to iteratively improve (better quality, faster for inference, other workflows, …)
In this role, you’ll build and implement novel Machine Learning and Deep Learning systems, as well as helping to build the infrastructure to train and deploy them. Specifically, you’ll: Design and implement the infrastructure required to train and run inference of models at scale. Build state-of-the-art deep learning and specifically Generative Adversarial Network (GAN) models. Work with the mobile development team to build real-time systems for model serving Work with the data team’s infrastructure to build real-time and offline feature databases As we grow, scale the ML system to be able to support more use cases and ML model types Qualifications & Requirements for ML Engineer Nice to have: Experience integrating with front end mobile systems, like React Native. Experience working with Google App Engine. Experience re-implementing deep learning models from papers. Especially previous work with GANs. One of the following: (a) BS or MS in CS or related field with 1+ years of experience in implementing and deploying large scale ML solutions (but honestly high school drop out is fine if you are a amazing dev). OR (b) Ph.D. in Machine Learning, Statistics, Optimization, Physics, or related field, with 1+ years experience building production-ready ML models and systems Strong software engineering fundamentals - understanding of data structures and algorithms, O-notation, ability to maintain a test suite and write clear maintainable code Familiarity with a majority of the following tools: Pytorch, Tensorflow, Numpy, Scipy, pandas, scikit-learn, Google App Engine. Strong programming skills in Python and ability to wrangle data from many disparate data sources Professional experience in either mobile development or full stack engineering Technologies we use: Pytorch, Swift, Google Clould Platform and AWS.