Requirements
- Expert Python skills
- Advanced Airflow experience
- Regular BigQuery experience
- Regular Snowflake experience
- Advanced Spark (Dataproc) experience
- Advanced Iceberg experience
- Regular AWS/GCP experience
- Strong production ML skills with proven track record of shipping models into real production pipelines
- Hands-on experience using classic ML to surface data quality issues at scale: unsupervised anomaly detection (kNN, Isolation Forest, autoencoders) and clustering on messy real-world tabular data
- Practical experience pairing classic ML with LLMs: using models to flag suspicious records and LLMs for reasoning, false-positive filtering, and final verification of anomalies
- Solid data engineering background across the modern stack (Airflow, Spark/Dataproc, BigQuery, Snowflake, Iceberg/Trino) and the production toolchain (GCP, Docker, Terraform, CI, MLflow)
- Pragmatic, product-oriented approach focused on incremental value delivery and seamless integration into existing workflows
- Professional fluency in English, enabling smooth technical and business discussions in an international environment
Additional Information
- Senior ML Engineer role
- Dynamic culture rooted in strong engineering, ownership, and transparency
- Empowers professionals to make a substantial impact in the software industry