Data Engineer (m/f/d) | Signatrix

Job description

Signatrix uses state-of-the-art deep learning and artificial intelligence technology to bring transparency and intelligence to brick and mortar retail. Thanks to our solutions, the security cameras of our clients can independently track, measure and evaluate customer behavior and patterns as well as theft incidents and conversion rates in real time.

Europe's biggest retail chains already enhance the processes and customer experience in their stores with the help of our solutions. Now that we have also secured funds by experienced investors, who will support us on a strategic and operational level, we are looking for a Data Engineer (m/f/d) to join our team.

Your tasks:

  • Offline and online pipelines for video and image data
  • Improve on internal Retail Environment Database (RED)
  • Optimize data structures and annotation processes
  • Build and iterate on the internal infrastructure for the collection, storage, annotation and processing of petabytes of data to train our models.
  • Build pipelines to automate the various steps in our ML workflows.
  • Work with ML engineers to design schemas and pick appropriate file formats to represent our training datasets
  • Build tools to support model experimentation and versioning


Your background:

Don't worry if you don't tick all of the below!

  • 2+ years of industry experience
  • B.Sc./M.Sc. or equivalent industry experience
  • Python, SQL/NOSQL databases, Docker
  • Experience with Professional software development processes and working with linux based systems
  • Ideally experience with scalable data processing systems like Spark/Hadoop, Kafka etc.
  • Experience with computer vision pipelines, distributed systems and data workflow management and automation tools preferred
  • C/GoLang/Haskell/Scala/Swift would be great!

What we offer:

  • Competitive salary
  • Possibility to earn shares in the company via ESOP
  • Lunch on the company
  • Public transport subsidy
  • Ability to take on responsibility early in your career and develop quickly