Job Title
Senior Machine Learning Engineer, Recommendation Systems
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About the Role
Create and implement machine learning models that power real-time recommendations for millions of users. Focus on personalization strategies to drive user engagement, retention, and revenue growth.
Responsibilities:
* Build, deploy, and maintain machine learning systems serving 100M+ predictions daily to personalize user experiences at scale.
* Enhance data processing pipelines with efficiency and reliability improvements using Spark, Beam, or Dask.
* Design ranking algorithms balancing relevance, diversity, and revenue goals.
* Deliver real-time personalization with latency under 50ms across key product surfaces.
* Run statistically rigorous A/B tests to measure business impact.
* Optimize for latency, throughput, and cost efficiency in production.
* Partner with cross-functional teams to launch high-impact personalization features.
* Implement monitoring systems and maintain ownership for model reliability.
Requirements:
* 5+ years building and scaling production ML systems with measurable business impact.
* Experience deploying ML systems serving 100M+ predictions daily.
* Strong background in ranking algorithms (collaborative filtering, learning-to-rank, deep learning).
* Proficiency in Python and ML frameworks (TensorFlow or PyTorch).
* Skilled with SQL and modern data warehouses (Snowflake, BigQuery, Redshift) plus data lakes.
* Familiarity with distributed computing (Spark, Ray) and LLM/AI Agent frameworks.
* Track record of improving business KPIs via ML-powered personalization.
* Experience with A/B testing platforms and experiment logging best practices.