We are searching for (Senior) Data Engineer
contextflow is an award-winning startup developing artificial intelligence-based software applications to support radiologists during clinical routine. Our team of deep learning and engineering experts use our own data flow framework for efficient deep learning development and benchmarking. Methods developed are aligned with data, annotation, clinical and IT requirements in mind and are deployed to hospital sites across Europe providing value in clinical routine to radiologists and patients.
As a (Senior) Data Engineer, you will
Be the curator of the datasets in the area of medical imaging and clinical data.
Plan, coordinate and execute the collection, preprocessing and analysis of these datasets.
Supervise the technical implementation of data labeling in cooperation with third parties, visualize annotations and makevalidated labelsavailable for machine learning.
Take responsibility for the processing pipeline right up to the machine learning models. This includes providing efficient access to images and metadata, managing data splits (train vs. test, research vs. product) and integrating labeling strategies (from volume to voxel level).
Join a deep learning team at the intersection of methodology, engineering of productive systems and medicine.
Be an active part of the R&D team in a culture of exchange and joint development of ideas.
What You Can Expect
You will be part of an interdisciplinary team, characterized by close collaboration and sharing of knowledge across boundaries of individual fields. We are focused on developing cutting-edge deep learning techniques that serve the rapidly-advancing needs of precision medicine and clinical practice. We put huge emphasis on the well being of all our team members. We take care and support each other so that we can grow together. We work hard but also enjoy spending time together. Every second Thursday, we have Happy Hour together. Feel free to ask about it in more detail in your interview : – )
Collaborate closely with the product design and development teams to link deep learning advances and user-facing features
Thrive in a young, dynamic learning environment where you can grow
Work directly with the founders and make meaningful contributions to company’s action and value
Manage your own time via flexible working hours
Enjoy other perks such as company retreats, public transport tickets, myclubs membership, etc.
Founded in 2016, we are one of the leading AI medical imaging startups, having grown to 23+ people. We work together with renown customers and industry partners across Europe.
What We Are Looking For
Familiarity with DICOM standard and medical data formats
Experience with Python and/or Julia or willingness to learn
Experience with modern software development processes & tools in UNIX environments
Data science basics (plotting, data visualizations, dealing with missing data during analysis)
Version control with git
Work permit in EU
Structured work style and high level of self-motivation
Fluency in English
Strong belief in growing together as a team
Empathy for each other
Understanding of general workflow in clinical routine
Work experience in the medical domain
Experience in natural language processing
Gross salary starting from 36,000€ annually, negotiablebased on experience. Open to both Senior and Junior levels.
We are an equal opportunities employer and value diversity! Females are strongly encouraged to apply.
Join an award-winning team
Science & Business Award 2016 – Rudolf Sallinger Fonds
Most Promising Startup 2016 – BCS Search Industry
Digital Innovation Award 2017 – Austrian Federal Ministry of Education, Science and Research
Philips HealthWorks 2018 – Chosen as one of 19 participants out of 700+ applications
Best Pitch 2019 (Healthcare) – Pioneers Festival
Best Healthtech Startup 2019 (Austria) – Central European Startup Awards
How to apply Interested? Send an email to firstname.lastname@example.org with max 1500 characters (~ half a page), letting us know why you would like to join contextflow and how you can best contribute.
Please provide links or attachments with information about yourself (CV, LinkedIN, Xing, website, github…).