What does the day-to-day of Data Python Engineer at Tomi.ai look like:
Every day we strive to improve the process of collecting and submitting data, as well as the quality of the data for our ML. To achieve this goal, we perform the following tasks:
- setting up the CI/CD process
- setting up monitoring and alerts (for example error statistics in input data)
- improving storage security
- building Data pipelines in the Kubernetes and Google Cloud environment
- work with BigQuery, BigQuery ML, and TensorFlow in Google Cloud
- development of microservices in Google Cloud for working with big data and building ML models
- development of microservices for data exchange via Marketing API (Facebook, Google, Yandex)
What does the ideal candidate look like:
- excellent data skills in Python / SQL / BigQuery
- experience with Kubernetes and Google Cloud, understanding the principles of microservice architecture
- experience in industrial development in Python with a focus on machine learning, data manipulation, and API writing from 3 years
- experience with pandas, scikit-learn, xgboost, TensorFlow libraries
- experience with Linux environment
- team player, confident, “getting things done”, independent, passionate and enthusiastic!
Why Tomi.ai?
We believe that building a great product and a great company starts with finding amazing people. At Tomi.ai you meet interesting, professional, and passionate people who really love what they do.
- we are open to new technologies and solutions, replacing complex things with simple ones. We do not have long formal agreements and strict vertical relationships
- each team member influences the success of Tomi.ai, so everyone has the opportunity to become a co-owner of the company
- we have no grades. The salary of each employee is set individually, based on the results of the interview
- it doesn’t matter what country and what city you live in. Our team works remotely
If you are interested in our idea, our values are close and you have the appropriate experience, knowledge, and skills, then: “Welcome to the team!”