ML Engineer (Python/Big Data)

Virtus Lab sp. z o.o. (Ltd.); Kraków; On-site; PLN 220,000 - 360,000; Full time

Job summary

VirtusLab in Kraków is seeking a Senior ML Engineer (Python/Big Data) to build production-grade ML solutions. You will ship models into real pipelines, collaborate with data engineering, and drive end-to-end data products.

The role requires strong Python, Airflow, BigQuery, Spark, and Iceberg expertise, plus experience with AWS or GCP. English fluency and a pragmatic, product-focused mindset are essential.

Qualifications

• Strong Python and production ML skills, with a 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 the 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.

Skills

Python

Airflow

BigQuery

Snowflake

Spark (Dataproc)

Iceberg

AWS/ GCP

Job description

VirtusLab is a leading European software consulting and engineering company. Our mission is to craft clean code and practical solutions with precision and purpose. We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering professionals to make a substantial impact in the software industry.

Senior ML Engineer (Python/Big Data)

Details:

• Python: Expert
• Airflow: Advanced
• BigQuery: Regular
• Snowflake: Regular
• Spark (Dataproc): Advanced
• Iceberg: Advanced
• AWS/ GCP: Regular

What we expect in general?

• Strong Python and production ML skills, with a 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 the 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.