Responsibilities * Developing pipelines that transform behavioral, demographic, and contextual data into real-time features; * Designing APIs and services for low-latency prediction and decision-making; * Implementing frameworks for A/B testing, exploration/exploitation strategies, and model evaluation; * Working closely with product and engineering teams to balance engagement, business value, and compliance; * Establishing monitoring, logging, and retraining workflows to continuously validate and improve models.
What we expect from you: * 5+ years of applied ML engineering experience (recommendation systems, personalization, ranking, or ads); * Strong background in Python and/or Go, SQL, and ML frameworks such as TensorFlow or PyTorch; * Experience deploying real-time ML systems (low-latency serving, feature stores, event-driven architectures); * Familiarity with cloud ML platforms (Vertex AI, SageMaker, or similar); * Experience with data warehouses (BigQuery, Snowflake, Redshift); * Understanding of multi-objective optimization and trade-offs in personalization; * Ability to thrive in a fast-paced, startup-style environment
Will be a plus: * Experience in martech, adtech, CRM, or large-scale consumer personalization; * Exposure to bandit algorithms or reinforcement learning; * Prior work on systems serving millions of users at scale; * Experience with Google Cloud Platform (GCP).
