Auf einen Blick
- Aufgaben: Join our Energy Optimization Team to develop machine learning algorithms for energy efficiency.
- Arbeitgeber: Green Fusion is an innovative energy tech startup focused on sustainable solutions.
- Mitarbeitervorteile: Enjoy flexible hours, remote work, and ongoing training opportunities.
- Warum dieser Job: Make a real impact in the fight against climate change while expanding your ML skills.
- Gewünschte Qualifikationen: Experience in machine learning projects, especially in time series forecasting or reinforcement learning.
- Andere Informationen: Be part of a dynamic team passionate about shaping the energy transition.
At Green Fusion, we combine digitalization and energy transition to create a sustainable future!
Our software optimizes heating systems in the real estate sector, tackling climate change through innovative digital solutions and automation. By reducing emissions and energy consumption, we are actively driving the energy transition forward.
As a Machine Learning Engineer (working student), you will support our Energy Optimization Team by conducting research and developing prototypes for machine learning and reinforcement learning-based energy optimization algorithms.
Tasks
- ML Research: Explore the latest literature on state-of-the-art machine learning concepts related to time-series prediction, digital twin modeling, and energy optimization algorithms.
- Time Series Forecasting: Collaborate with our ML team to develop prototypes for forecasting heating demand and PV production using state-of-the art ML models, and evaluate different approaches.
- Digital Twin Modeling: Assist in creating state-of-the-art data-driven models for heating systems.
- Reinforcement Learning (RL) Algorithms: Support the training of RL agents to optimize the operational control of heat pumps for optimal efficiency.
- Algorithm Development: Contribute to the design and implementation of innovative algorithms that improve energy management and efficiency.
- Collaboration: Work closely with energy engineers, ML engineers, and data scientists to develop innovative features for our smart home energy management system.
- Clear Communication: Effectively present findings and insights in a concise and understandable manner, ensuring clarity for all stakeholders.
Requirements
- You are currently enrolled as a student at a university
- You are able to work at least one day in our office in Berlin
- You have proven experience in at least one personal machine learning project, ideally in areas like time series forecasting, digital twin modeling, or reinforcement learning.
- You bring strong skills in statistics, machine learning, data modeling, data processing, and data cleaning, with particular expertise in working with time series data.
- You are proficient in Python, Git, Pandas, SciPy, Scikit-Learn, and PyTorch/TensorFlow. Your programming style is clean, well-structured, and maintainable, making it easy for team members to understand and collaborate.
- Proactive and eager to learn, you have a genuine interest in technical topics and enjoy sharing knowledge with others.
- You communicate complex insights clearly to a range of stakeholders and foster a collaborative team environment.
- You are fluent in English and have a basic understanding of German.
Benefits
📈An opportunity to expand your skill set in machine learning and reinforcement learning by training models with real production potential!
🏠 Flexible working hour models, home office, and remote work.
💡 Ongoing training opportunities – whether through job challenges, our open feedback culture, or sponsored training programs, there are always opportunities to learn and grow.
💼 Employee benefits such as Urban Sports Club or Become1.
🌱 Direct impact through your job – with us, you can actively contribute to the energy transition and fight against climate change every day.
💚 We value our team – that’s why regular team events are very important to us.
🙌 The best team that Berlin has to offer – and maybe even beyond. Don’t believe it? Then find out for yourself and apply now!
—
While we are still considered pioneers today, we can soon dominate the market with you! First in the DACH region, then throughout Europe.
You can expect a motivated, open-minded, and dynamic environment that is passionate and ambitious about actively shaping the energy transition – a goal that can only be achieved together!
We look forward to your application – Fernanda will get in touch with you!
Machine Learning Engineer (Working Student) in Energy Tech Start Up (f/m/d) Arbeitgeber: Green Fusion GmbH
Kontaktperson:
Green Fusion GmbH HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Machine Learning Engineer (Working Student) in Energy Tech Start Up (f/m/d)
✨Tip Number 1
Familiarize yourself with the latest trends in machine learning, especially in time-series forecasting and reinforcement learning. This will not only help you during interviews but also show your genuine interest in the field.
✨Tip Number 2
Engage with online communities or forums related to energy optimization and machine learning. Networking with professionals in these areas can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss your personal machine learning projects in detail. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this demonstrates your problem-solving skills.
✨Tip Number 4
Practice clear communication of complex technical concepts. Being able to convey your findings effectively to non-technical stakeholders is crucial in a collaborative environment like Green Fusion.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Machine Learning Engineer (Working Student) in Energy Tech Start Up (f/m/d)
Tipps für deine Bewerbung 🫡
Understand the Company: Familiarize yourself with Green Fusion's mission and values. Highlight your passion for sustainability and how your skills align with their goal of driving the energy transition.
Showcase Relevant Experience: Emphasize your personal machine learning projects, especially those related to time series forecasting, digital twin modeling, or reinforcement learning. Provide specific examples of your contributions and outcomes.
Highlight Technical Skills: Clearly list your proficiency in Python, Git, Pandas, SciPy, Scikit-Learn, and PyTorch/TensorFlow. Mention any relevant coursework or certifications that demonstrate your expertise in machine learning and data processing.
Communicate Effectively: Demonstrate your ability to present complex insights clearly. Use concise language in your application to ensure that your findings and experiences are easily understood by a diverse audience.
Wie du dich auf ein Vorstellungsgespräch bei Green Fusion GmbH vorbereitest
✨Showcase Your Projects
Be prepared to discuss your personal machine learning projects in detail. Highlight your experience with time series forecasting, digital twin modeling, or reinforcement learning, and explain the challenges you faced and how you overcame them.
✨Understand the Energy Sector
Familiarize yourself with the energy sector and current trends in energy optimization. This will help you demonstrate your genuine interest in the field and how your skills can contribute to the company's mission of driving the energy transition.
✨Communicate Clearly
Practice explaining complex machine learning concepts in simple terms. Since you'll be collaborating with energy engineers and other stakeholders, clear communication is key to ensuring everyone is on the same page.
✨Demonstrate Team Spirit
Emphasize your collaborative mindset and eagerness to learn from others. Share examples of how you've worked effectively in teams, as this role requires close collaboration with various professionals to develop innovative solutions.