Overview

Required Qualifications:

  • 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

Nice to Have

  • 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