We are looking for a Principal ML Engineer.
Work on core data and machine learning infrastructure, which is at the heart of offering. You will create innovative solutions for data ingestion and normalization from multiple data sources, feature engineering and feature selection, as well as actual model training and evaluation. All in large scale and completely automated.
Requirements: 10+ years experience as a Machine Learning Engineer.
15+ years of experience with Python/Java/Scala.
Strong understanding of distributed systems, object-oriented programming and design pattern
Distributed Compute frameworks such as Spark, Dask, Ray etc
Experience with REST APIs, server-side API integration, queues and distributed systems.
Knowledge of ORM, SQL and Data Modeling.
Understanding of system design and knowledge of system design patterns.
Experience with microservices architecture.
Previous experience in E2E design and implementation of features as part of large scale backend projects.
MLOps
Hands-on experience with open source ML libraries like: catboost, lightgbm, xgboost, scikit-learn, NumPy, Pandas, Microservices architecture, cloud technologies, Docker/K8s.
Ability to design and own a feature through all its phases.
Bonus:
BSc./MSc. In CS or similar an advantage
Building data pipelines using Apache Airflow
Hands on experience with Spark, SparkSQL, Spark streaming and other Spark related projects
This position is open to all candidates.
