We are looking to expand our team to include a full-time machine learning engineer. Our product is a service for mobile that can authenticate a user actionlessly and continuously, yet remain completely invisible to the user experience. The core is a deep network that is trained over behavioral observations of the authorized user, and can authenticate that user given a short window of behavioral observations. This product is already live with first customers and we have much more in the pipeline.
You'll be working directly with the founding team on our core product. Your day to day will be a mix of straight-up data science (non-deep ML work) and applying new deep learning techniques from image, video and voice processing research to behavioral data. You will also be integrating improvements and advances into the product and rolling it out to customers. The team is a mix of machine learning engineering, deep learning, software architecture, cybersecurity, systems, and mobile engineering skillsets.
Deep learning for behavioral data is a brand new field with us at the forefront, and we have strong connections into the academic research groups in the space. This is one of the few problems where machine intelligence greatly outperforms human intelligence. Authentication provides us with automatic label generation, endless sources of data, and the opportunity to apply cutting edge techniques to a new field in a live product environment.
- Masters level education or higher in a ML-related field
- Strong ML fundamentals (ability to apply core fundamentals to new problems)
- Enough ML experience to have an intuitive understanding of how things work.
- Previous experience (either academic, private sector or personal interest) working with convolutional and recurrent neural networks.
TWOSENSE.AI is changing the way we authenticate ourselves to the devices we interact with. In human interaction, authentication between friends is implicit: it's a function of the shared experiences and behavior that make up our identity and how we identify each other. However, when we authenticate to devices it's still a password-based handshake.
Our product is an Enterprise SaaS solution for invisible, continuous, multi-factor authentication based on behavior. It learns to recognize the authorized user for an account using the way they walk, pick up a device, type, swipe, move the mouse and many more aspects of their behavior.
We are a team with Ph.D. machine learning expertise, years of enterprise application building experience and a leadership background in cybersecurity who are making device authentication as seamless as saying hello to an old friend through behavior-based authentication.