Subfamily Description

At Nokia, we are dedicated to staying at the forefront of technology and innovation. We are looking for a motivated and tech-savvy working student to join our team and help integrate Artificial Intelligence (AI) and Machine Learning (ML) into our existing processes. This is an exciting opportunity to gain hands-on experience in a dynamic and forward-thinking environment.

- Currently enrolled in a Bachelor's or Master's program in Computer Science, Data Science, Engineering, or a related field in Germany.

- Strong interest in AI/ML technologies and their applications in business.

- Basic understanding of machine learning algorithms and data science principles.

- Proficiency in programming languages such as Python, R, or Java.

- Experience with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn) is a plus.

- Strong analytical and problem-solving skills.

- Excellent communication and teamwork abilities.

- Ability to work independently and manage time effectively.

Workplace: Germany, ULM

Work is on site/hybrid

AI/ML Research and Development:

   - Assist in identifying potential applications of AI/ML within the organization.

   - Conduct research on current AI/ML trends, tools, and technologies.

   - Develop proof-of-concept models to demonstrate the feasibility of AI/ML applications.

Data Preparation and Analysis:

   - Collect, preprocess, and analyze data relevant to AI/ML projects.

   - Work with large datasets to extract meaningful insights and patterns.

   - Collaborate with data scientists to ensure data integrity and accuracy.

Model Development and Testing:

   - Assist in designing, developing, and testing AI/ML models.

   - Evaluate model performance and fine-tune algorithms to improve accuracy.

   - Implement best practices for model validation and deployment.

Integration and Deployment:

   - Support the integration of AI/ML models into existing systems and workflows.

   - Collaborate with IT and software development teams to ensure seamless implementation.

   - Monitor and maintain deployed models to ensure continuous performance.

Documentation and Reporting:

   - Document AI/ML processes, methodologies, and project outcomes.

   - Prepare and present reports on project progress and findings.

   - Create user manuals and guides for AI/ML tools and applications.

Collaboration and Communication:

   - Work closely with cross-functional teams to understand business needs and objectives.

   - Communicate complex technical concepts to non-technical stakeholders.

   - Participate in team meetings and contribute to brainstorming sessions.