Sr AI/Machine Learning Analyst

Design, train, and deploy production‑grade ML models, including text classification, anomaly detection, and image classification. 

Own the full ML lifecycle—from experimentation and validation to deployment, monitoring, and continuous improvement. 

Build and maintain scalable data pipelines for preprocessing, validation, and transformation of large datasets. 

Ensure ML systems are reliable, observable, and scalable in high‑volume production environments. 

Collaborate closely with Engineering, Product, and Anti‑Fraud teams from problem definition to delivery. 

Implement and optimize ML algorithms using Python and frameworks like TensorFlow, PyTorch, and Scikit‑learn. 

Optimize model and system performance in cloud environments, particularly AWS. 

Promote best practices in experimentation, reproducibility, monitoring, and documentation. 

Experience building and deploying ML systems in production. 

Strong Python skills and hands‑on experience with ML libraries (Scikit‑learn, TensorFlow, PyTorch). 

Experience with large‑scale data processing frameworks (e.g., Databricks, Spark). 

Experience designing and maintaining production ML pipelines. 

Solid understanding of system design, scalability, and reliability. 

Experience with cloud platforms (preferably AWS). 

Strong problem‑solving skills and ability to work autonomously. 

Advanced or fluent English. 

Experience with large‑scale text classification, anomaly detection, or image classification. 

Background in fraud detection or high‑risk/high‑volume environments. 

Familiarity with orchestration tools (Airflow, Dagster). 

Experience with Docker and Kubernetes. 

Experience working with Lakehouse architectures.