Auf einen Blick
- Aufgaben: Design and deploy ML models for energy optimization and predictive analytics.
- Arbeitgeber: Join a young PropTech startup focused on sustainable building operations.
- Mitarbeitervorteile: Earn competitive pay starting at 21 €/h with flexible work options and wellness benefits.
- Warum dieser Job: Make a real impact in reducing CO2 emissions while growing your machine learning skills.
- Gewünschte Qualifikationen: Must be in your 5th semester or higher in Informatics, proficient in Python and ML frameworks.
- Andere Informationen: Apply with your resume, transcript, and a note on why you're a perfect fit.
The building sector is responsible for 40 percent of CO2 emissions in Germany, making it the largest contributor. Moreover, we spend most of our time indoors, which gives us all the more reason to operate buildings in a way that keeps people at the center, both now and in the long term. As a young PropTech startup, we are committed to exactly this goal: to operate buildings in an automated, reliable, and sustainable manner. With our intelligent building control system, we are on the path to achieving a climate-neutral building stock by 2045.
As a Working Student/Intern Machine Learning (m/f/d), you will work closely with top experts in their field, gaining invaluable hands-on experience with innovative technology developed over five years of research. You’ll have the opportunity to deepen your machine learning skills by contributing to cutting-edge projects in energy optimization and predictive analytics.
Aufgaben
What You’ll Work On:
- Design and deploy ML models for energy optimization and predictive analytics, integrating solutions that are both robust and efficient.
- Develop, test, and implement cost-effective, real-time energy management strategies.
- Optimized Workflows with CI/CD and MLOps by streamlining data handling, feature engineering, and model management to improve efficiency.
- Build predictive models for real-time device health monitoring, boosting uptime and reducing maintenance costs.
Qualifikation
Who We’re Looking For:
- You’re in your 5th semester or higher in a Bachelor’s or Master’s program in Informatics or a related field.
- Proficiency in Python and ML frameworks (TensorFlow, PyTorch) is essential.
- Familiarity with scalable architectures and DevOps tools (like Docker, Kubernetes, or Kubeflow) is a plus.
- You’re proactive, highly organized, and driven to push boundaries to set new standards in ML.
Benefits
Why baind AG:
- Your Impact: Join us in transforming the building sector, responsible for 40% of Germany’s CO₂ emissions and drive toward a climate-neutral future by 2045.
- Your Chance: Join as one of the first team members in our ML team, taking on opportunities to grow with a high-impact startup that just closed a successful seed round and is ready to take off with you.
- Competitive Pay: Starting at 21 €/h, with the potential for a raise after six months based on performance.
- Comprehensive Resources: Access our in-house compute cluster for model training and fine-tuning.
- Flexible Work Environment: Choose between macOS or Linux, work up to 50% remotely, and benefit from flexible hours.
- Work-Life Balance: Enjoy a Wellpass membership with access to over 10,000 sports and wellness facilities across Germany.
Apply with your resume, your current grade transcript, and a brief note on why you’re a perfect fit. Specify if you’re applying for an internship, working student role, or thesis project. We are looking forward to your application!
Important Notice:
We will only consider applications that include all required documents. Note that our application system allows you to upload only two files: one for your CV and one for your cover letter or other supporting materials. Ensure that you combine all relevant documents into these two files before submitting your application. Once submitted, changes or additions to your application cannot be made.
Working Student/Intern Machine Learning (m/f/d) Arbeitgeber: baind AG
Kontaktperson:
baind AG HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Working Student/Intern Machine Learning (m/f/d)
✨Tip Number 1
Familiarize yourself with the latest trends in machine learning, especially in energy optimization and predictive analytics. This knowledge will not only help you during the interview but also show your genuine interest in the field.
✨Tip Number 2
Engage with the PropTech community by attending relevant meetups or webinars. Networking with professionals in the industry can provide insights and potentially lead to referrals.
✨Tip Number 3
Showcase any personal projects or contributions to open-source initiatives related to machine learning. This practical experience can set you apart from other candidates and demonstrate your hands-on skills.
✨Tip Number 4
Prepare thoughtful questions about the company's mission and projects during the interview. This demonstrates your enthusiasm for their goals and your desire to contribute meaningfully to their team.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Working Student/Intern Machine Learning (m/f/d)
Tipps für deine Bewerbung 🫡
Understand the Company Mission: Familiarize yourself with the company's commitment to sustainability and climate-neutral building operations. Reflect this understanding in your application to show alignment with their goals.
Highlight Relevant Skills: Emphasize your proficiency in Python and machine learning frameworks like TensorFlow or PyTorch. Mention any experience with DevOps tools, as these are crucial for the role.
Tailor Your Application: Customize your resume and cover letter to reflect the specific responsibilities and qualifications mentioned in the job description. Clearly state your interest in either the internship or working student role.
Showcase Your Projects: Include any relevant projects or coursework that demonstrate your machine learning skills and experience with energy optimization or predictive analytics. This will help you stand out as a candidate.
Wie du dich auf ein Vorstellungsgespräch bei baind AG vorbereitest
✨Showcase Your Machine Learning Knowledge
Be prepared to discuss your experience with machine learning frameworks like TensorFlow and PyTorch. Highlight any projects you've worked on that involved designing or deploying ML models, especially in energy optimization or predictive analytics.
✨Demonstrate Proactivity and Organization
Since the company values proactive and organized individuals, share examples from your past experiences where you took initiative or improved processes. This will show that you align with their expectations.
✨Familiarize Yourself with CI/CD and MLOps
Brush up on your knowledge of CI/CD practices and MLOps tools such as Docker and Kubernetes. Be ready to discuss how these can streamline data handling and model management, as this is crucial for the role.
✨Express Your Passion for Sustainability
Given the company's commitment to climate neutrality, convey your enthusiasm for sustainable practices in the building sector. Share any relevant experiences or projects that reflect your dedication to this cause.