ML Engineer (AdTech)

B3 Consulting Poland is part of an international organization listed on NASDAQ in Stockholm, operating in 11 countries with full autonomy in Poland, selecting technologies, processes, and ways of working independently while maintaining high standards. They execute IT projects in Poland and internationally, focusing on thoughtful experience development.

• Proficiency in software engineering fundamentals and production coding standards, emphasizing modular and maintainable architecture.
• Experience deploying and maintaining ML models in production, including automated monitoring and incident resolution.
• Advanced knowledge of MLOps including automation of model lifecycles, CI/CD, and release management.
• Familiarity with cloud platforms (preferably GCP) for handling ML data and workloads at scale.
• Advanced knowledge of Python and SQL for ML engineering tasks such as orchestrating training and supporting inference.
• Deep understanding of DevOps principles and Site Reliability Engineering (SRE) applied to ML systems.
• Ability to use AI-assisted coding tools to enhance engineering productivity and maintain code quality.
• English language proficiency at B2+ level.

Nice to have:

• Experience in AdTech, ranking, or ML-based recommendation systems.
• Experience with distributed data and feature processing pipelines (e.g., Vertex Pipelines, Dask, or Spark).
• Knowledge of cloud serving ecosystems, microservice architectures, and cross-language model integration patterns.
• Experience with feature stores and mechanisms ensuring consistency between training and serving.

• Build and maintain production ML services in the advertising domain, ensuring operational stability in a high-traffic AdTech platform.
• Orchestrate ML Engineering processes including model lifecycle management, packaging, deployment strategies, and observability.
• Collaborate with Data Science and Research teams.
• Work on the GCP platform in a containerized environment using Vertex AI, BigQuery, and Cloud Storage for large-scale ML workloads.
• Participate in on-call and incident management.