Launch Potato

Senior Machine Learning Engineer, Recommendation Systems

Launch Potato

full-time

Posted on:

Origin:  • 💃 Anywhere in Latin America

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Job Level

Senior

Tech Stack

Amazon RedshiftBigQueryPythonPyTorchRaySparkSQLTensorflow

About the role

  • Design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys
  • Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale
  • Enhance data processing pipelines (Spark, Beam, Dask) for efficiency and reliability
  • Design ranking algorithms that balance relevance, diversity, and revenue
  • Deliver real-time personalization with latency <50ms across key product surfaces
  • Run statistically rigorous A/B tests to measure true business impact
  • Optimize for latency, throughput, and cost efficiency in production
  • Partner with product, engineering, and analytics teams to launch personalization features
  • Implement monitoring systems and maintain ownership for model reliability
  • Own modeling, feature engineering, data pipelines, and experimentation workflows

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 with 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
  • Experience with experimentation infrastructure (MLflow, W&B)
  • Experience with feature engineering, data pipelines, and model deployment at scale