freiberufler Machine Learning Engineer | Interactive Data Visualization auf

Machine Learning Engineer | Interactive Data Visualization

  • 80€/Stunde
  • 71384 Weinstadt
  • auf Anfrage
  • de  |  en
  • 16.10.2020


Hallo, ich bin M. - ein leidenschaftlicher Data Nerd & Full Stack Developer.
- Fullstack Entwicklung in der Cloud (Amazon Web Services)
- Data Analysis & Machine Learning (pandas, sklearn, tensorflow)
- Interactive Data Visualization (d3.js)

Ich biete

  • Amazon Web Services (AWS)
  • Angular
  • Cloud (allg.)
  • JavaScript
  • Machinelles Lernen (allg.)
  • Natural Language Processing (NLP)
  • Node.js
  • Python
  • Scikit-learn
  • SQL

Projekt‐ & Berufserfahrung

Freelance Machine Learning Engineer
ReachNow, Remote
3/2020 – 6/2020 (4 Monate)

3/2020 – 6/2020


Map Matching of vehicle position data
Input: Billions of noisy vehicle telemetry data points (position, direction etc.)
Output: Vehicle trajectories matched to street
The algorithm is scheduled periodically on AWS Batch to process historic telemetry data stored on S3. I used GraphHopper Map Matching and implemented a Particle Filter that leads to matched trajectories of high quality. The quality of the processed trajectories is measured and can be monitored using AWS CloudWatch.
AWS Batch, Lambda, S3, CloudWatch, Docker, Python, Pandas, OSM, Graphhopper

Eingesetzte Qualifikationen

Pandas Datenrahmen, Docker, Git, Python, Amazon Web Services (AWS)

Freelance Machine Learning Engineer
ReachNow, Remote
12/2019 – 2/2020 (3 Monate)

12/2019 – 2/2020


Frontend and Backend for managing models / clusters for a Fleet ML service
A UI (and Backend for the Frontend) was built to make an ML solution easy to expand to new cities and easy maintanable. The UI makes it possible to manage and extend the services for people that are not deeply involved into the technical details. A specialty about the project is the storage of the meta data (cities, clusters, POIs) via GitHub API to allow the 4-eyes principle via GitHub PRs and enable versioning and rollbacks.
AWS ECS, S3, Docker, GitHub API, Python, ol3js, Vue.js, tailwindcss

Eingesetzte Qualifikationen

Docker, Git, Python, Amazon Web Services (AWS), JavaScript, Vue.js

Freelance Machine Learning Engineer
ReachNow, Remote
9/2019 – 11/2019 (3 Monate)

9/2019 – 11/2019


Interactive Vehicle ETA prediction visualization.
For a shuttle service 3 different estimations of arrival time (ETA) are used. To track their performance over time and by the given circumstances these ETAs were collected and compared by their actual arrival time. An interactive visualization (Backend & Frontend) was created to analyze the different ETAs.
data collection: AWS Lambda, S3
backend: AWS ECS, Docker, Python Flask
frontend: Vue.js, ol3js, d3.js

Eingesetzte Qualifikationen

Docker, Git, Python, Amazon Web Services (AWS), JavaScript, Vue.js

Head of Data Science (Festanstellung)
moovel Group GmbH, Stuttgart
10/2015 – 8/2019 (3 Jahre, 11 Monate)

10/2015 – 8/2019


After our company (ROOMAPS) and team was acquired by moovel Group we started to migrate our Indoor Navigation Stack to the moovel Maps technologies. Also we further extended our technologies to indoor mapping via Tango devices and 3D rendering of buildings. In July 2016 I started my journey as a Machine Learning Engineer in the Data Science Team building projects like Bus Delay Prediction, Demand Prediction for Shuttle services and intelligent relocation of shuttles based on estimated demands.

Eingesetzte Qualifikationen

Machinelles Lernen (allg.), Pandas Datenrahmen, TensorFlow, Docker, Git, Python, Amazon Web Services (AWS), Angular, JavaScript

ROOMAPS | Founder & Software Engineer
Rhenus, Daimler Financial Services, Universität St, Stuttgart
6/2012 – 5/2015 (3 Jahre)

6/2012 – 5/2015


Co-Founder of ROOMAPS as an innovative indoor navigation & information system for smartphones with individual map-design and modern technology for positioning indoors.

The core of the ROOMAPS technology consisted of:

Map Import & Rendering. Import map features based on AutoCAD files and store as PostGIS geometries. The tile server renders the tiles on-the-fly when requested. Served through AWS CloudFront they are cached for the next requests. For rendering the Java Topology Suite and GeoTools have been used.

Navigation Mesh Building & Routing. Based on the walkable area a navigation mesh (a graph which consist of convex connected Polygons) is created automatically. This is used for the A* routing algorithm to find shortest pathes.

Indoorpositioning. An extensible approach of a particle filter and Map Matching based on Navigation Meshs was used to get the positioning of a smartphone. Depending on the environment all the available information a smartphone can gather was fed into the algorithm to improve its accuracy: Acceleration, Gyro, Magnetic Field, Bluetooth, WiFi, Barometers.

Eingesetzte Qualifikationen

PostgreSQL, Android Entwicklung, Docker, Git, Amazon Web Services (AWS), AngularJS


Computer Vision Nanodegree
April 2019
Udacity Artificial Intelligence Nanodegree
Februar 2019
Udacity Deep Learning Nanodegree Foundation
Juli 2017


(Diplom Informatiker)
Jahr: 2011
Ort: Stuttgart


Cloud: AWS S3, Lambda, EC2, ECS, Batch, Kinesis, RDS, SimpleDB, Cassandra, CloudWatch
Data: Pandas, NumPy, Scraping (scrapy, beautifulsoup), Spark
Machine Learning: scikit-learn, PyTorch, Tensorflow, xgboost, CatBoost
Backend: REST APIs, Docker, Git, SQL, Python, Node.js, Java
Frontend: Javascript, React, Vue, Angular, d3

Über mich

Hallo, ich bin M. - ein leidenschaftlicher Data Nerd & Full Stack Developer & Entrepreneur.

Seit meiner Schulzeit liebe ich die Entwicklung von Webanwendungen. Heute bin ich mehr denn je davon begeistert, wie Technologie Dinge ermöglicht, die vor weniger Zeit undenkbar waren.

Meine aktuellen Schwerpunkte:
- Fullstack Entwicklung in der Cloud (Amazon Web Services)
- Data Collection (Public Data, Spatial Data, Site Scraping, API scraping)
- Machine Learning (XGBoost, scikit-learn, PyTorch, Tensorflow)
- Interactive Data Visualization (d3.js)

Haben Sie spannende Projektideen und wollen diese schnell und kompetent umsetzen?
Dann kontaktieren Sie mich für ein unverbindliches Beratungsgespräch.

Persönliche Daten

  • Deutsch (Muttersprache)
  • Englisch (Fließend)
auf Anfrage
9 Jahre und 7 Monate (seit 03/2012)


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