Software has been "eating the world" for the past decade. Recently, a new phenomenon has started to emerge: machine learning is eating softw...
Software has been "eating the world" for the past decade. Recently, a new phenomenon has started to emerge: machine learning is eating software (Software 2.0). This calls for new tools in the ML development stack to massively improve efficiencies, reduce costs and mitigate data biases across healthcare, financial services, insurance etc.
At Galileo, we are building a next generation ML data-centric stack to address this problem. Our team comprises product and engineering leaders from Uber Michelangelo, Google AI, Stanford AI Lab and Carnegie Mellon. We are backed by AI execs from Apple and leading academics from Stanford.
About this opportunity
As an early engineer at Galileo, you will work alongside leading industry and academic experts to play a foundational role in designing, building, and scaling our products and team.
We're looking for an exceptional Senior Machine Learning Engineer, interested in solving complex problems at the intersection of Data and ML.
Ideally you have:
- A startup mindset, biasing towards thoughtful action with minimal direction.
- 3+ years of experience building ML products
- Experience building, testing, and experimenting with ML models using unstructured data.
- Great curiosity about the latest ML research.
- Excellent communication skills, especially when it comes to sharing results of your research and experiments with your team in order to inform product development.
- Hands-on experience with popular ML frameworks (like PyTorch, TensorFlow, Keras).
- Extensive experience with git and GitHub - it's almost second nature for you.
- Bonus: Experience working with ML related services in AWS, Google Cloud, or Microsoft Azure.
We are based out of the San Francisco Bay Area and are open to building a distributed team too. Come join us!