SF | NY | REMOTE

Who we are

Pixelcut is one of the most popular design tools in the US. Over 30 million small businesses, creators and entrepreneurs use Pixelcut to create content for their business. We build world-class products at the intersection of AI and creativity, making tools like Background Removal and Magic Eraser accessible and easy-to-use for millions of people.

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We’re a team of builders inspired to bring AI-powered creative tools to small businesses around the world. We believe AI will revolutionize all aspects of creativity inside of companies, and we want to make this future a reality today. If you’re excited to build this future, we’d love to talk with you.

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A few other tidbits about us and our culture:

• We are fully remote which means you can work on your schedule.
• We are a diverse team and believe this helps us create the best products for everyone. We encourage applications from all candidates.
• We hire self-motivated experts which allows us to minimize meetings and syncs and lets you do what you do best, which is create and build!

The Role

• This is a pivotal role where you will work closely with our research scientists to transform cutting-edge machine learning models into production-ready systems that serve millions of users.
• You’ll build and maintain robust tools to support model training, manage large datasets, and streamline the ML lifecycle, enabling the team to work more efficiently and effectively.
• You will be responsible for deploying and optimizing ML models, ensuring they are scalable, reliable, and perform at a high level in production environments.
• You’ll take ownership of backend infrastructure to support ML operations, troubleshooting and resolving issues as they arise to ensure seamless performance.
• This role will have significant impact, allowing you to enable the ML team to focus on innovation while you provide the infrastructure and tools that bring AI-powered creativity to life.

Who you are

• You’re an experienced Backend Engineer with a strong background in deploying and scaling machine learning models in production environments.
• You have a deep understanding of backend technologies and are proficient in Python and PyTorch.
• You have experience handling large datasets, and are comfortable working in cloud environments.