Machine Learning Engineer
Position
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.)

Contract Type
B2B / Full Time Job

Level
Medior/Senior

Location
Prague/Full remote

Salary
150- 320 EUR/MD

Industry
IT

Requirements
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