Who You Are

• You have 4+ years of experience in developing backends in Python in Django and FastAPI
• You have experience with asynchronous processing tools, like Celery
• You have a strong knowledge of best practices in backend development
• You are well versed in making systems scalable and robust
• You have experience with Docker and Kubernetes
• You have experience with both SQL and noSQL databases
• Bonus points if you have an understanding of basic Machine Learning and MLOps concepts
• And bonus points if you have experience in working under Linux systems
• Your preference is to work in a highly collaborative environment 
• You’re comfortable with feedback - you take it like a champ, implement it with efficiency, and deliver it with tact
• You know how to be resourceful in order to get things done
• You have an open mind to using the technology that will produce the best results

O stanowisku / o projekcie 

You might have known us as Shelfwise before, today as Image Recognition by FORM we aim to build the world's best image recognition platform for smarter retail execution. Our solution leverages machine learning to provide data and analyses about products and prices on physical shop shelves - in real-time. We are ambitious, we are striving for success, we create amazing things!

Zakres obowiązków

1. You will be at the forefront of developing the Machine Learning infrastructure and tools behind ShelfWise + FORM.com, as we enter the next chapter of the company’s storyYour competence will allow us to improve value added with our Image Recognition capabilities 
2. You will develop critically important backend pieces for our Machine Learning systems, that will bring in new functionalities as well as scalability, robustness and high level of automation to our systems like: tools for training data acquisition and data processing, analyzing images in real-time by multiple AI models, a tool for evaluating models’ performance 
3. Automatic AI models lifecycle: training, evaluation, deployment, continuous accuracy monitoring 
4. Development and maintenance of image processing tools: training data acquisition, analyzing images in real-time by multiple AI models, evaluating models’ performance 
5. Taking active part in crucial discussions and team decisions 
6. Cooperating with Machine Learning, Web, Mobile and IoT teams 
7. Experimenting with new technologies and tools