As a data scientist you will push the boundaries of deep learning & NLP by conducting research in cutting-edge AI and apply that research to production scale data. Our data includes a large corpora of global patents in multiple languages and a wealth of metadata. The focus of your work will be to analyze, visualize, and interpret large text corpora as well as more traditional structured data. This includes recommending and implementing ML-based product features. We also expect to publish primary research and contribute to FOSS that we use.
This is an exciting opportunity to part of a startup that is applying deep learning to a real-world problem at global scale. We’re always looking for leaders and there is room to grow for the right person to take increasing responsibility working as part of a small and dynamic team.
Tokyo, Melbourne, San Francisco (willing to negotiate remote work as well)
Architect and implement software libraries for batch processing, API-based predictions, and static analyses
Rapidly iterate on the design, implementation and evaluation of machine learning algorithms for document corpora
Report and present software developments including status and results clearly and efficiently, verbally and in writing
Participate in strategy discussions about technology roadmap, solution architecture, and product design
Strict adherence to clean code paradigms
Minimum Qualifications and Education Requirements:
BSc/BEng degree in computer science, mathematics, machine learning, computational linguistics or equivalent (MSc/MEng preferable)
Experience with implementing statistical methods and data visualization
Good knowledge of computer science principles underpinning the implementation of machine learning algorithms
Experience with deep learning approaches to NLP, particularly RNNs
Experience implementing deep learning models in TensorFlow or PyTorch
Contributions to open source projects
Passion for new developments in AI
Experience with GCP or AWS
A track record of machine learning code that is:
To apply, please contact us at firstname.lastname@example.org with your CV.