What you'll be doing - System Design and Architecture: Develop and maintain robust, scalable, and efficient distributed systems and data pipelines to help build the new generation of ironSource's ML feature platform.
- Research and Innovation: Stay current with the latest advancements in machine learning data pipelines, feature stores, and apply innovative techniques to improve data aggregations, monitoring, cleaning & filtering and preparing for ML training.
- Cross-Functional Collaboration: Work closely with data scientists, software engineers and product managers to build the data lakes and data pipelines.
What we're looking for - Proficiency in programming languages such as Scala/Java.
- Hands on experience in streaming technologies (Kafka, Kinesis, SQS).
- Expert in big data processing frameworks such as Apache Spark, Trino, Flink.
- Data Lake management knowledge: table formats (Iceberg, Delta). Data-warehouses (Redshift, Big Query, Snowflake)
- MLOps systems - Model registry, Experiment Tracking (MLFlow, W&B), Feature Store management (Feast, Tecton), Workflow management (Kubeflow, Airflow)..
- Knowledge of microservices architecture and event-driven design.
You might also have
- experience with ML frameworks such as TensorFlow, PyTorch.
- experience with high scale distributed systems.
- Proficiency with cloud platforms such as AWS, and experience with containerization technologies like Docker and Kubernetes.
Additional information
- Relocation support is not available for this position.
- Work visa/immigration sponsorship is not available for this position
This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.