Gretel

Gretel is at the forefront of synthetic data generation, offering a platform that empowers developers to create artificial datasets mirroring the characteristics of real data. This innovation enables the development and testing of AI models without compromising sensitive information or privacy. We're disrupting the data landscape, making AI development accessible and secure. We leverage cutting-edge technologies like generative AI and privacy-enhancing technologies (PETs) to deliver our platform. Our tech stack includes Python, deep learning tools, and LLMs to build the software behind our core product. We're a remote-first company with a highly collaborative culture that values transparency and employee autonomy. We believe in fostering an environment where engineers and scientists can thrive and make a real impact. Our mission is to unlock the potential of sensitive data for AI development and analytics, ensuring both privacy and utility. We're a rapidly growing company, backed by significant funding, and our team members are subject matter experts who are passionate about innovation. We are deeply collaborative, apolitical and mission-oriented. Our team members enjoy autonomy, trust, and the tools needed to act like owners. We're currently looking for talented machine learning engineers to join our Applied Science team, to help unlock real-world use cases for synthetic data generation that our enterprise customers are working on today, including models that can better detect heart disease across genders and ethnicities, financial models that can better respond to unseen data and market changes, and safe datasets that enable medical researchers to share data on rare diseases without compromising patient identity. We are an equal opportunity employer and are committed to creating an inclusive environment for all candidates and employees. We encourage you to apply if you are looking for an environment that thrives on collaboration, innovation, and a commitment to engineering excellence.