DataArt Company Profile

AI/ML Developer


Opis pracy

About the vacancy

DataArt is engaged in IT, AI/ML, and data consulting and software development. Since 1997, we have been designing, developing, modernizing, and supporting solutions that help the businesses of our clients grow. DataArt started as a company of friends and continues to cultivate a unique culture that distinguishes it from other IT companies, such as:- Flat structure. There are no “bosses” and “subordinates”;- We hire people not for a project, but to the company. If the project (or your work in it) is over, you go to another project or on a paid “Idle”, where you develop your skills;- Flexible schedule, ability to change projects, work from home, and diverse opportunities to try yourself in different roles, working with different clients on different projects;- Minimal bureaucracy and micro-management, convenient corporate services.


Must have

  • Strong knowledge and skills in at least one AI/ML domain: CV, NLP, ML, Mobile ML, MLOps, Chatbots, etc.
  • Proven ability to implement and debug ML models in either industry or an equivalent academic setting
  • Strong knowledge of programming languages for ML/DS (at least one of): Python, R
  • Experience in production troubleshooting using Kibana, Splunk, cloud monitoring tools
  • Working knowledge of containers (Docker)
  • Working experience with ML/DS products (at least one of): TensorFlow, PyTorch, AWS Sagemaker, Databricks, DataRobot, Keras, XGBoost, Jupiter Notebooks
  • Business sense when suggesting and implementing solutions
  • Excellent communication skills
  • Spoken English


Would be a plus

  • Strong theoretical background in ML
  • CI/CD tools and practices (one of): Git, Jenkins, TeamCity, Travis CI, etc.
  • ML serving tools (one of): Kubeflow, MLFlow, MetaFlow, TFX (TensorFlow extended),
  • Data visualization: Power BI, Tableau
  • ETLs Tools (one of): Airflow, Luigi, Azure Data Factory, AWS Glue
  • Data: Relational Databases (Oracle, MS SQL, MySQL, Postgres, etc.), Non-SQL (Mongo), DWH, Data Lakes, Snowflake, Kafka, Kinesis
  • Cloud (one of): AWS, Azure, GCP
  • On-device and embedded ML: TensorFlow Light, Core ML
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