NOTE: We can only consider applicants who are willing and able to relocate to NYC and are permitted to work in the US.
TWOSENSE.AI is looking to expand our team to include a full-time mobile engineer. We are at the intersection of mobile applications, machine learning, and cybersecurity. Our product is a mobile service (mobile library and cloud backend) that learns the behavior of an authorized user and provides persistent and continuous authentication to the client application. We’re looking for someone who believes machine learning and behavioral data will bring about a paradigm shift in how we securely access the myriad of devices we interact with every day.
You will be working directly on our core product, which consumes mobile sensor data, processes it and passes it to an embedded deep neural network to authenticate the user. You will work with all manner of sensor (time-series) data, such as the accelerometer, gyroscope, magnetometer, proximity, screen usage, temperature, light, etc. We will be expanding our capabilities together, focusing on data processing pipelines, reducing power consumption, and cloud backend connectivity and data synchronization.
You’ll be joining a team of Ph.D. machine learning experts with years of enterprise application building experience and solid backgrounds in cybersecurity.
What we’re looking for:
* 5+ years professional experience
* Expert in Android SDK (Java).
* Experience with background/foreground services.
* Experience with Android NDK or any native C++ development
* Experience with unit and instrumentation testing, preferably Test-Driven Development.
* Experience with TEE (TrustZone).
* Background in security and encryption.
* Motion-based gaming/AR/VR development.
* Experience with motion sensors (IMU / accelerometer).
* AWS and APIs.
* Machine Learning / Data Science.
* Experience with IPC & AIDL.
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.