Machine Learning Engineer

📋 Description

• Build end-to-end ML pipelines for large-scale data.
• Train merchant-specific models and serve low-latency predictions.
• Develop production ML ecosystems with streaming telemetry.
• Write high-performance code to minimize scoring latency.
• Collaborate with Infra, PM, and Data Science to translate fraud signals.

🎯 Requirements

• 4+ years building and deploying large-scale ML models in production.
• Proficient in Java or Scala and Python.
• Databricks; Spark, Flink, or Hadoop; Bigtable NoSQL.
• Statistical modeling, ML algorithms (XGBoost, RF, NN).
• System design in distributed, multi-tenant cloud (GCP).
• Bonus: Fraud detection or cyber-security domain experience.

🎁 Benefits

• Diverse, equitable, inclusive workplace.
• Transparent recruitment privacy.
• Remote-friendly with flexible work.