ML Engineer (Python/Big Data)
- Role
- AI / ML
- Experience
- Senior
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No BS summary
Senior ML Engineer with strong Python and production ML skills, experienced in shipping models to production. Must have hands-on experience with unsupervised anomaly detection and clustering on messy data, and practical experience pairing classic ML with LLMs for anomaly verification. Requires a solid data engineering background and professional fluency in English.
Core skills
Required skills
Required languages
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: Required skills: 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.
What you'll do
- 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.
What they require
- Strong Python and production ML skills, with a proven track record of shipping models into real production pipelines.
- Professional fluency in English, enabling smooth technical and business discussions in an international environment.
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.