Gretel is a startup founded by engineers from AWS and Google to help developers to safely and quickly experiment, build, and collaborate with data. At Gretel, we believe that access to data needs to become easier, more accessible, and safe. We are innovating with machine learning to help developers make sense of complex data, and privacy-enhancing technologies to streamline developer access to data safely. We are looking to hire highly skilled machine learning engineers to join our rapidly growing team- working across topics including synthetic data generation, natural language processing, data privacy, bias and fairness.

Are you an experienced machine learning engineer with a strong desire to work on products that help other engineers get the most out of their day? Do you want to help engineering teams develop new capabilities by leveraging their data more effectively? Want to work as part of a remote, distributed team? If so, please join us!

Responsibilities

• You will be involved in end-to-end development, exploring new applications and techniques within NLP, synthetic data generation, and privacy.

Minimum qualifications

• M.S. or PhD in Computer Science, related technical field or equivalent practical experience.
• A strong understanding of fundamental concepts in deep learning and related mathematics.
• The ability to quickly implement infrastructure, iterate on it, and evaluate it empirically.
• Strong communication skills - you speak, and write, your mind well. We’re a distributed team so we’re extra mindful about communication
• Experience working with distributed systems.
• At least 5 years of professional experience in software development.

Preferred experience

• Experience building applications with Python and/or Go
• Experience with ML frameworks such as Tensorflow, HuggingFace, Pytorch
• Experience with ML algorithms such as Transformers, LSTM, RNN, language models, NLP
• Experience working remotely in a distributed company

We also value

• An interest in data visualization, interfaces, and experience using web technologies to build them. We believe that the ability to build visualizations and interfaces is a huge enabler in studying neural networks.