Student trainee in Machine Learning - Focus on Sustainability
YOUR ENVIRONMENT AND TEAM
Are you passionate about machine learning, software engineering, and the application of AI for sustainable use cases? Then join our Sustainability Management Platform team and help us relieve the workload of sustainability managers with modern ML- and LLM-based systems. You will contribute to the development of AI components, data pipelines, and modeling logics that help our customers make informed and sustainable decisions.
YOUR AREA OF RESPONSIBILITY
- You will support the development of our AI systems (including LLM-based approaches, embeddings and retrieval methods) to accurately calculate carbon footprints and other sustainability indicators.
- You will develop and optimize Python code for data pipelines that integrate our emission factor database into existing systems.
- You work with SQL to analyze, validate, and prepare data for use in machine learning models.
- You will support data modeling and the automation of accounting methods, ensuring that these comply with current standards.
- You will support our Product Owner and the Machine Learning team with customer-specific research, prototyping and modeling tasks.
WHAT YOU BRING
- You are currently enrolled in a Bachelor's or Master's degree program in Computer Science, Data Science, Mathematics, Physics or a comparable field of study and have at least one year of study time remaining.
- You have good Python skills and a solid understanding of the fundamentals of machine learning (e.g., model training, evaluation, and common algorithms). Which framework you have used previously is less important to us than your fundamental understanding.
- You have already worked with Large Language Models (LLMs) or implemented your own projects (e.g. with prompting, RAG systems or embeddings) and would like to further deepen this knowledge in practice.
- You have good SQL skills for data analysis and ETL processes.
- You are interested in sustainability topics. Initial experience in CO₂ accounting (e.g., according to the GHG Protocol or ISO standards) or with emission factor databases (e.g., ecoinvent or GaBi) is advantageous, but not mandatory.
- You have very good English skills, both spoken and written.
- You can support us 2-3 days per week.
THIS IS WHAT YOU CAN EXPECT!
At pacemaker, we combine the innovative power of an agile SaaS startup with the advantages and stability of an established corporation. We foster an open and collaborative work environment where we share our knowledge across teams and celebrate successes together.
- Remote-First-Culture: In addition to the freedom to work from anywhere in Germany, you can work from other EU countries for 20 days a year.
- Offices: If you're in the mood for an office atmosphere, you're welcome to drop by our office in Münster anytime. Meetings also take place in Munich, Berlin, Düsseldorf, and Hamburg.
- Flexible working hours: Design your workday according to your needs – without fixed core working hours, as long as it is compatible with your daily business & team.
- Team Days: Our Team Days promote exchange outside of everyday life, allow new employees to get to know the team and strengthen our corporate culture.
- Equipment: You will work with a powerful MacBook that offers optimal support in your daily work.
- Further education: With our Udemy Pro access, you get unlimited access to further education courses in your field and can thus develop yourself optimally in your area.
- Other benefits: thyssenkrupp pension plan, bicycle leasing, corporate benefits and many more extras await you!
We value diversity and therefore welcome all applications regardless of gender, gender identity, nationality, age, disability, ethnic origin, religion/belief, or sexual orientation.
We look forward to receiving your application!
About Us
At pacemaker.ai, we are passionate about developing AI-based solutions to sustainably improve our customers' supply chains. We combine data and expert industry knowledge to use artificial intelligence to create precise forecasts and detailed CO₂ balances. This empowers our customers to make informed decisions for a more cost-effective, efficient, and sustainable supply chain.
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