Job Requirements
This job post is managed by
Keefe Lim
Last active 2 years ago
Job description for Full Stack Developer Intern at Reality Detector
Come join Reality Detector (Seer) – a deep-tech startup seed funded by Tim Draper and Draper Associates which is creating AI-powered deception and emotion detection technology to “reveal incongruent words and actions at a glance”. Our vision is to augment human understanding through technology and mission is to build a deception indicator and convince skeptics. To achieve this, we are i) augmenting and commercializing accurate behavioral science with rule-based AI and ii) automating novel automated deep-learning. Our initial product market fit is in creating cutting-edge biometrics to enhance travel across borders and protect innocents from harmful lies. The Full-Stack Developer Intern will be working in a small team including data scientists and software developers to develop the subsequent versions of our computer vision software, especially the audio and NLP features.
Responsibilities
- Assists in development of frontend and backend features for application
- Develop scripts to enable automated integration, delivery and deployment of the application
- Define, implement and automate tests to ensure that the functional, performance and security requirements are met
- Ensure quality assurance and testing of your deliverable
Qualification
- Experienced with RESTful web services design and development
- Detailed knowledge of at least one modern JavaScript framework
- Proficient in Python
- Familiar with relational and non-relational databases e.g. MySQL, MongoDB
- Familiar with version control systems e.g. Github
- Able to work independently and efficiently
Qualities
- Share in our purpose to create a world where all people can access undistorted reality and accurately place their trust in others, ensuring authenticity, realism and credibility in human interactions.
- Have a growth mindset, be conscientious and be willing to set stretch goals for yourself.
- Be open to new ideas and feedback from others and believability-weighted decision making.