AI Engineer
2018 - 2020jumio- Detected if a document had a fraudulent physical manipulation while keeping a false positive level below 0.001% (one wrong in 10,000 samples).
- Developed a simple model to detect if a decent quality document is present or not. This was achieved with >98% true positive with a false positive below 0.001%.
- Extracted and analyzed BI-related information to the other AI-engineers.
Technologies: PyTorch, TensorFlow, PythonIT Consultant
2018 - 2018Sigma - Ericsson- Developed tools for Ericsson's continuous integration system and added new functionalities to ensure better code from developers.
- Tracked and fixed various bugs using Jira as a reporting tool.
- Maintained tools for Ericsson's continuous integration system.
Technologies: Bash Script, Jenkins, PythonIT - Consultant
2017 - 2018Sigma - Ascom- Implemented continuous integration workflow for Ascom's message server by simulation android devices and message loss to ensure 99.999% reliability.
- Automated short tests on each commit, mainly to test that the code still runs and works properly.
- Automated a long load test to verify the complete system including Android devices and message serving.
Technologies: Bash Script, Jenkins, Git, Android Debug Bridge, Pytest, PythonSoftware Engineer in Test
2011 - 2014Saab AB- Extended functionality in a control system for an airborne ground/foliage penetration radar system. Mainly made it possible for developers to be able to use new functionality while doing field tests.
- Developed test system for JAS-Gripen Radar system using various hardware such as network analyzer, to gather data to later perform test and verification of hardware of the next generation of flight radar.
- Extended and improved functionality for test rig to perform verification tests on big radar systems. Including finding bugs and improvements that saved the users over a week of work.
- Built test applications to help developers to test and verify functionality and performance of Advanced LIDAR systems, this included a user interface where the user could control the whole system.
Technologies: Network Analysis, System Testing, Electronics, LabVIEW, MATLAB
Henrik Svensson
Deep Learning Developer in Montreal, QC, Canada
Member since August 25, 2020
Henrik is a machine learning engineer with 5+ years of work experience and several years of experience in developing software as a hobby. He likes to think outside the box and creatively solve complex problems. He has advanced programming proficiency in multiple languages, including Python and C++. Henrik's recent interests are in the machine learning field, where he currently holds two years of professional experience using both TensorFlow and PyTorch.
Henrik is now available for hire
Portfolio
- jumioPyTorch, TensorFlow, Python
- Sigma - EricssonBash Script, Jenkins, Python
- Sigma - AscomBash Script, Jenkins, Git, Android Debug Bridge, Pytest, Python
Experience
- Git 6 years
- Python 5 years
- Pandas 4 years
- TensorFlow 3 years
- Machine Learning 2 years
- Deep Learning 2 years
- PyTorch 1 year
- Agent-based Modeling 1 year
Availability
Part-time
Preferred Environment
PyTorch, TensorFlow, Python, VS Code, Linux
The most amazing...
...project I've worked on was a project in behavioral cloning during a nanodegree in self-driving cars from Udacity.
Employment
Experience
- Capstone Data Scientist Nanodegreehttps://medium.com/@henriksvensson_1896/starbucks-analysis-of-simulated-data-c033e210a4d1
As part of my nanodegree as a data scientist at Udacity, I used simulated historical Starbucks data, analyzed what makes users buy an item, and what offers to send them. This was for my last and final capstone project.
- Semantic-Segmentation for Self-Driving Carhttps://github.com/henrisve/CarND-Semantic-Segmentation
Using a fully convolutional network to classify each pixel in a video stream, to detect whether or not it is a drivable road. This was done using TensorFlow, part of Udacity's nanodegree in self-driving cars.
Skills
Languages
Python, Bash Script, Python 3Libraries/APIs
TensorFlow, PyTorch, Keras, PandasTools
VS Code, Pytest, Git, Android Debug Bridge, Jenkins, MATLAB, LabVIEWParadigms
Agent-based Modeling, CRISP-DM, ETLPlatforms
Linux, Amazon Web Services (AWS)Other
Machine Learning, System Testing, Path Planning, Deep Learning, Robotics, Information Theory, Electronics, Network Analysis, AWS, Robot Operating System (ROS), Sensor Fusion, Localization, Recommendation Systems, funkSVD, ELT
Education
- Master's Degree in Complex Adaptive Systems2014 - 2016Chalmers University of Technology - Gothenburg, Swedem
Certifications
- Data Scientist (Nanodegree)MAY 2020 - PRESENTUdacity
- Self-Driving Cars (Nanodegree)JULY 2019 - PRESENTUdacity
