About the position
Checkout Technologies is a start-up in Milan, Italy. We disrupt UX in Retail eliminating the queues and checkout delays. We base our system on the computer vision and artificial intelligence.
Build infrastructure for transforming raw data (GBs per week) into a labelled dataset for training models. You will also automate and scale out these workflows to enable ML engineers to rapidly experiment and iterate on our suite of deep learning models that make automated checkout possible. As an early engineer on the data team, you will become an expert on all our computer vision datasets: where the data lives, what the data means, and how to find it, extract it, and version it using production-quality code and rigorous data standards.
- Create models that analyse metadata for anomalies and identify hard cases for the current state of the technology
- Build and iterate on the internal infrastructure for the collection, storage, annotation and processing of terabytes of data to train our models.
- Build pipelines to automate the various steps in our ML workflows.
- Work with ML engineers to design schemas and pick appropriate file formats to represent our training datasets
- Build tools to support model experimentation and versioning
- Setup DevOps pipeline for faster and more reliable build, test and release of our machine learning models
Skills & requirements
- Experience level: Mid-Level, Senior-Level
- Proficient with bash, python or golang
- Knowledge of the machine learning tools (scikit-learn, scipy) and image processing libraries (opencv, matplotlib) is a plus
- Experience with data processing systems like Kafka, Spark/Hadoop etc.
- Experience with SQL (PostgreSQL), NoSQL (MongoDB, Elasticsearch) and object (e.g. Ceph) data stores.
- Experience with data workflow management and automation tools such as Airflow, MLflow.
- Knowledge of the containerization and virtualization (Docker, Docker Swarm, Kubernetes)
- Problem solving
- Be ready to gain momentum in the fast growing company
- Compensation (€40k - 50k)
- Modern tech equipment
- Grow quickly in a top-level team
- Attend Conferences and Courses
- Awesome co-workers