Machine Learning Engineer

This client is a middle-sized company with a challenging vision and an enthusiastic team. Our ambition is to help other businesses to turn the data to their advantage - we stand for AI-based data aggregation and data profiling as well as digitisation and automation of processes. We've been developing great products that could be seamlessly integrated into core corporate systems. Now we are searching for a new colleague to our industry-oriented team that will help us to reach our mission.

Work duties:

• coding, testing, and debugging

• creating, modifying, and applying machine learning algorithms in innovative ways on the industrial topics

• exploring datasets, designing data pipelines, creating visualizations, and creating end-to-end ML solutions

• providing valuable data insights to address the customer business challenges using visualization

• communicating with project stakeholders (with technical and non-technical) and explaining them selected approach

• optimalization, scraping, vizualization

• influencing the direction of client's product development

Why should you work for our client?

• Nice opportunity to work in a German company (and DACH customers)

• Own innovative product

• Non-corporate culture

• Remote working culture

• Flexible business hours (the candidate should fit within 6-18 time-frame)

• English is the business language

Benefits:

• Innovative mind

• Flexibility in working culture

• Friendly and motivated team

• System of benefits

• Educational system

Other information:

• They use agile methodology

• Scrum

• 2-week sprints

• 70 team members are located in Czechia (developers, testers, data scientists, etc.)

Must-have stack:

• Fluent in Python and SQL + experience with Pandas, NumPy, Sklearn, Matplotlib/Seaborn, Git 

• Algorithms and applied statistics knowledge, ability to design and write scalable algorithms for various complex problems

• Machine Learning

• • Knowledge of a computational framework such as TensorFlow, Pytorch

  • Experience with Keras or similar high level APIs

• Optimization

• • Knowledge of basic optimization techniques and gradient descent and back-propagation

  • Knowledge of commonly used loss functions/metrics and their properties (RMSE, MAE, MAPE, crossentropy, etc.)

• Visualization skills

• Experience with data structures

• Intermediate knowledge of graph theory

• Experience with docker

• Fluent communication in English (written + spoken) 

• Highly appreciated is hands-on experience from the industry, knowledge of ERP or PLM systems

Nice-to-have stack:

• Linux administration skills

• Knowledge of C/C++ and cython

• Knowledge of Rust, R and Java

• Experiences with Kubernetes

• Experience with Julia

• CI/CD v Atlassian stack (Bamboo, Bitbucket)

• German language