Senior Machine Learning Engineer (Recommendation Systems & Personalization)

Responsibilities:

• Develop real-time product and bundle recommendation engines, including dynamic slot placement optimized for conversion and margin.

• Build targeted promotion algorithms: personalized coupon and points issuance, behavioral triggers and dynamic bundling.

• Scale the multi-market customer segmentation engine (behavioral, demographic, psychographic and lookalike audiences, wallet push).

• Extend personalization models across web, app and in-store employee touchpoints.

• Build and operate ML pipelines, from feature preparation in BigQuery and Snowflake to deployment and monitoring.

• Design and evaluate A/B tests to prove the business impact of each model.

Requirements:

• Hands-on experience building ranking or recommender systems that run in production.

• Strong Python and SQL skills; experience with TensorFlow or PyTorch.

• Solid grounding in model evaluation and validation, both offline metrics and online results.

• Experience designing and analyzing A/B tests and experiments.

• MLOps experience: ML pipelines, model deployment, performance monitoring and CI/CD.

• Experience with cloud data warehouses, ideally BigQuery and/or Snowflake, and pipeline orchestration with Airflow.

• Experience with real-time or low-latency model serving.

• Experience with promotion, pricing or uplift modeling (e.g. coupon targeting, bundling).

• Customer segmentation and lookalike modeling across several markets.

• Infrastructure as code with Terraform.

• Experience on GCP ML tooling such as Vertex AI.

• Background in retail or e-commerce personalization.

• Fluent English for working in an international team.

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