remote
Machine Learning Engineer - Sardine
ML Engineer
Lead end‑to‑end ML development for a real‑time fraud detection platform, building scalable models, feature pipelines, and deployment workflows on AWS to protect millions of users from financial crime.
About the role
Key Responsibilities
- Design, develop, and production‑grade deploy ML models for fraud detection and AML using Python, TensorFlow/PyTorch, and AWS SageMaker.
- Build and maintain feature pipelines, data ingestion workflows, and feature stores to support real‑time scoring.
- Collaborate with data scientists, data engineers, and security analysts to refine model performance and reduce false positives.
- Implement monitoring, logging, and automated retraining pipelines to ensure model drift mitigation.
- Document model logic, data lineage, and performance metrics for compliance and audit purposes.
Requirements
- 3+ years of ML engineering experience in a production environment.
- Strong proficiency in Python, SQL, and AWS services (S3, Lambda, SageMaker, Glue).
- Hands‑on experience with feature engineering, model training, and deployment pipelines.
- Knowledge of fraud detection, anomaly detection, or related security domains is a plus.
- Excellent communication skills and ability to work cross‑functionally in a fast‑paced startup.
Skills
pythonmachine learningawssqltensorflow