You’ll be working wherever we need you:
- picking items from the warehouse
- packing items
- preparing stock for storage
- receiving goods
- cleaning warehouse and shelving areas, etc.
The especially good thing is:
After your initial training, you can start working at whatever daytime you want to. In the morning, in the afternoon or in the evening, even during the night. We have work to be done nearly 24/7. We agree on a timing but you can tell us when it's best for you and we try to make it happen.
Important:
Whilst working, you are required to wear a head-mounted camera, which we use to record our manual tasks for the training of humanoid robots. For useful footage (billed to the nearest minute), you will receive an additional €3 per hour on top of your hourly wage.
Studentische Mitarbeit Pick&Pack/Lager/Reinigung - Student Job Pick&Pack/Warehouse/Cleaning (m/w/d)
Straubing
Part-time
Working Student
14.60 € per hour
Your mission
Your profile
You are a student (m/f/d) and are looking for a job where you can set your own hours. You do not need to speak German (but you do need at least a basic knowledge of English).
About us
Flowerbox is an online retailer based in Straubing, specialising in plants, bouquets, floristry supplies, and home décor. We combine a wide product range with fast delivery – from live plants to cut and dried flowers, right through to professional floristry supplies. Flowerbox is operated by Flowerbox GmbH, based in Straubing (Leipziger Str. 6).
We are a team that doesn’t merely manage growth but drives it forward: pragmatically, data-driven and with a clear focus on execution. To this end, we consistently utilise AI where it delivers genuine efficiency – and expect the same mindset in this role: identifying levers for improvement, testing them, refining them and scaling them up. Ultimately, what counts for us is not the activity itself, but the result.
We are a team that doesn’t merely manage growth but drives it forward: pragmatically, data-driven and with a clear focus on execution. To this end, we consistently utilise AI where it delivers genuine efficiency – and expect the same mindset in this role: identifying levers for improvement, testing them, refining them and scaling them up. Ultimately, what counts for us is not the activity itself, but the result.