Sr. ML Engineer

Job Description

REQUIREMENTS

• 8–9 years of hands-on ML engineering experience shipping and operating production systems at scale.
• Proven experience in the media, advertising, or audience activation industry.
• Proficiency with Databricks (including MLflow and Spark), Snowflake, and Azure (ADLS, Azure ML, AKS).
• Expert-level Python and SQL skills.
• Strong knowledge of applied statistics, such as sampling, forecasting, or experimental design.
• A degree in Computer Science or a related engineering field.
• Ability to work during the second half of the day to overlap with a US-based product team.

Preferred

• Experience with Docker, Kubernetes, and orchestration tools like Airflow or Dagster.
• Knowledge of Ad tech/identity concepts including DSP/SSP, DMP/CDP, and clean rooms.
• Familiarity with AWS or GCP environments.

RESPONSIBILITIES

• Convert data science prototypes into reproducible, production-quality ML services.
• Build and operate large-scale data and feature pipelines using Databricks, Spark, and Snowflake.
• Own the full model lifecycle, including MLflow tracking, CI/CD, automated retraining, and drift monitoring.
• Engineer the activation layer for governed delivery of segments and scores into DSPs, SSPs, and programmatic partners.
• Ensure system scalability, latency, cost-efficiency, and reproducibility within an Azure environment.
• Enforce privacy-by-design principles, including data minimization and encryption.

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