Providing support in design and implementation of an AI platform to be integrated into a test stand of a Life Science application
Collecting experimental data to feed the machine learning solution developed and test with acquired data
Improving the ML model according to test data outcomes
Adapting the ML pipeline to changes in experimental hypothesis
Participating in the cross-discipline design process for system design, combining your skills with HW and SW team members
Development of front end applications for pilot runs of the proof of concept
Supporting positive team interactions to accomplish program objectives
Contributing to schedule & milestone commitments based on an agile framework

Enrolled in bachelor’s or master's degree in Computer Engineering, Robotics, Electrical or Software Engineering
Strong analytical/problem solving skills and ability to use statistical tools and techniques
Knowledge in machine learning libraries and frameworks such as Numpy, Panda Tensorflow /Pytorch, Sci-kit Learn
Familiarity with machine learning mathematical models like SVM, Linear Regression, Decision Trees, Neural Networks
Moderate to high proficiency in Python
Knowledge of algorithms and data structure
Proficiency in Visual Studio and preferred text editor for Python
Familiarity with source control systems for example Git and Github
Knowledge of interfacing sensors/hardware with microcontrollers like Raspberry Pi, STM 32, Arduino
Familiarity with computer interface protocols for example Serial (RS232/RS485), I2C and SPI, and USB as well as Ethernet communications protocols such as TCP/IP, Modbus and HTTP

Hands-on practical experience
Opportunity to work with experienced professionals in an innovative engineering environment

Engineering Intern – Software Machine & Operations

Key skills