At Hypefactors, we are working together designing and building the best software tools for Public Relations professionals across the globe. Our software is beautiful, data-intense and smart. And our unique data offering and advanced analyses create big business impact for our users.

Our data pipelines dig deep into online news, blogs, social media, TV radio and traditional print from nearly all countries on the planet. We receive double-digit millions media elements each day, with over 100 data points for each media element. These unique data pipelines provide us with an unprecedented opportunity to transform raw data into business advantages for our clients. We collaborate with the IT University of Copenhagen on these data challenges and setting the new frontier in data sciences and AI. 

This position is in the Hypefactors Engineering team and you’ll be reporting directly to the CTO. Our engineering team is technically cross-functional, with expertises in digital design, embedded systems, backend, frontend, mobile, data engineering and data sciences. We function in a DevOps-manner and strive to improve ourselves through process-improvement, adopting and devising best-practices while doing scientific R&D in collaboration with universities.

We look for the kind of engineer who adapts to change and initiates change, thus thriving in an environment characterized by continuous progress. We let our users’ needs push us solving challenging and worthwhile engineering problems.

Key Responsibilities

• Involve in high-priority account management for identifying business automation and intelligence needs
• Design, improve and operate AI algorithms utilizing machine learning and probabilistic models
• Coordinate with fellow-engineers its integration with the backend, frontend and mobile apps

• Mentor graduates and (junior) engineers
• Manage key product features
• Strategic technology roadmap planning
• Engineering data pipelines

Basic Qualifications

• Scala
• Applied machine learning and/or probabilistic programming to prior business projects
• MSc or PhD in computer science, mathematics, statistics, economics or other engineering/sciences

Desirable

• Experience with data pipeline engineering
• Natural language processing
• Experience with hybrid AI solutions using cloud services and in-house models
• Experience with DevOps fundamentals

Your Application

Instead of a cover letter, please describe your role in the most interesting professional work result where you applied machine learning and/or probabilistic programming. Also inform us of a recent white paper or scientific article in the area of AI or data sciences you’ve read and elaborate why you’ve been fascinated by it. Send this, along with your resume through the Hub.