ML Engineer - Working Student

Job Description:

Working Student is a long-term paid internship that allows you to kickstart your fabulous journey in the IT and Telecom world. As our Trainee you can have experience working in such areas that correspond to full-time engineering jobs. The internship usually lasts from 6 to 24 months. We are open to flexible working hours so that you can reconcile working with us with your studies. #OpenToYou.
Position: Machine Learning Engineer - Working Student
Duration: 12 months (possibility to prolong to the next 12 months)
Date: 1.09.2025-30.08.2026
Location: Poland (hybrid in Wroclaw)

Education Recommendations: Computer Science, Data Science, Automation and Robotics or similar
Join our team, where you'll design, develop, and deploy cutting-edge ML models that bridge data science and software engineering. Collaborating with experts, you'll transform prototypes into scalable solutions that drive innovation and enhance our competitive edge in the 6G market. Leverage state-of-the-art GPU technology to accelerate model training and inference while tackling large datasets and complex computations.

As part of our team, you will:
* Design and implement machine learning models to solve specific business challenges
* Clean, preprocess, and transform raw data for effective model training and evaluation
* Train models using appropriate datasets, ensuring accuracy through thorough evaluation metrics
* Collaborate closely with data scientists and engineers to integrate ML solutions effectively
* Document models and processes thoroughly for knowledge sharing and future reference

Candidate Requirements:

You have :
* Active student status
* Good English (written and spoken)
* Knowledge of machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn
* Good skill in Python programming language
* Familiarity with version control systems like Git
* Understanding of statistical methods and mathematical concepts in machine learning
* Knowledge of various model evaluation metrics and techniques
It would be nice if you also had:
* Knowledge of 5G networks, particularly the physical layer
* Experience in managing project timelines and deliverables
* Familiarity with model development and optimization
* Awareness of GPU programming techniques