About Leuko:

Leuko, an MIT and UPM spin-out, is developing the world’s first non-invasive white blood cell monitoring device. White blood cell assessment is a first-line indicator for various medically-relevant situations, ranging from chemotherapy management to the detection of life threatening infections worldwide. This test is currently invasive and not readily accessible - it requires patient travel, blood draws and laboratory infrastructure. This currently limits the frequency of monitoring, which puts patients’ health, and even lives, at risk. Leuko is re-imagining the way to perform these tests without extracting blood and in a portable device. Leuko’s vision is to empower patients and their loved ones, and make their lives better and safer by providing them with broad and immediate access to blood testing. In 2018, our company was awarded 1st prize at the Startup Worldcup, MassChallenge HealthTech and Sanitas Disruptive competitions.

About the position:

• Full-time position (40 hours/week)

• Start date: as soon as available

Responsibilities:

• Integrate novel or refined computer-vision and machine-learning-based methods for automated video/image analysis into an existing production-level codebase

• Evaluate overall performance of these methods on datasets, and develop specific unit tests where needed 

• Retrain, reparameterize, optimize, and/or adapt these methods depending on their compliance with the regulatory requirements on regularly updated datasets

• Develop new computer-vision and machine-learning-based methods for automated video/image analysis to enhance test accuracy and expand it to other blood parameters

• Work collaboratively with, and at the interface between, the algorithms and the software-development team

• Nurture a friendly and safe working environment

Basic Qualifications:

• Bachelor’s or Master’s degree in computer science, computer engineering, software engineering, information systems or equivalent

• Experience in computer vision: image/video/signal analysis/processing, with publication/project track record, involving methods such as image registration, object detection, object tracking, peak detection, or similar

• Proficiency and demonstrated good practice in production-level code development with Git/GitHub

• Proficiency in numerical computing languages, with  Julia (julialang.org) and Python preferred

• Self-directed, proactive, and detail-oriented, with a strong, independent work ethic, ability to effectively communicate with both technical and non-technical members of the team and to deliver code quickly

• Fluency in English (C1 level or above on the CEFR scale) and experience working with a diverse cross-functional international team

Preferred Qualifications:

• Experience with AWS cloud computing, data storage technologies, and cost optimization

• Knowledge of machine learning, deep learning, and/or object-detection methods

• Experience with medical images, medical devices, and/or digital health

• Strong familiarity with up-to-date academic literature

• Experience working with remote developer teams

• Experience in CI testing implementation