Senior Computer Vision Engineer

Job description

As a Computer Vision Engineer, you are a part computer scientist and a part research engineer. 

You have an analytical mindset, a deep understanding of linear algebra and statistics, and provable hands-on programming experience. You will be part of the Applied A.I. team and you are passionate about computer vision, machine learning, deep learning, and data science in general. You will work on interesting projects for some of the world's most innovative clients and partners as well as work on internal technologies

  • You love a high growth work environment with a diverse team.
  • Your main objective will be to help our customers by building and integrating Computer Vision models for classification, anomaly detection, object recognition and/or tracking
  • You will be responsible for designing and implementing state-of-the-art methods for creating computer vision pipelines, including preprocessing, streaming, sampling, and overseeing data annotations.
  • Your ability to understand and implement state-of-the-art academic research papers will help you to apply novel algorithms to large volumes of real-life data.
  • You will help the team to improve upon current methods and models. You have a practical mindset and are able to bring these models into a production environment. As such, you have extensive experience with Python or another relevant programming language.
  • You will work closely together with other ML engineers, Python developers, Fullstack Developers, and DevOps engineers.

Job requirements

  • You have a master’s degree or Ph.D. in computer science, computer vision, machine learning, artificial intelligence, mathematics, or a related field. Demonstrable equivalent experience is fine too.
  • You have provable experience in computer vision, image recognition and/or deep learning
  • You have good knowledge of and experience with the Python stack including Tensorflow or Pytorch, darknet, OpenCV
  • You have experience with standard software development tools like git, Jira, bash, RegEx, ...
  • You have a practical mindset and are willing to get your hands dirty. You understand the difference between fundamental research and data-driven development.
  • You consider yourself a healthy mix between a machine learning expert, a software engineer, a researcher, and a hacker.
  • You are fluent in English.
  • You can work independently and take matters into your own hands.
  • The ability to quickly learn new technologies and successfully implement them is essential

Experience with any of the following is considered a plus:

  • Cloud platforms like Microsoft Azure, Google Cloud Compute, and Amazon AWS
  • Docker, Kubernetes, TF Serving, continuous integration, microservices architecture, ...
  • Open-source contributions