Machine Learning Engineer

AI Talent Hope is seeking an experienced Machine Learning Engineer to build and deploy production-grade ML systems for real-time fraud detection. The role involves developing scalable solutions that power critical fraud prevention systems, working across machine learning, backend engineering, and data pipelines.

Responsibilities:

• Build and optimize real-time data pipelines and backend services
• Develop, deploy, and maintain production ML models for fraud detection
• Engineer production-ready features from large-scale datasets
• Collaborate with backend and platform engineers
• Ensure security, privacy, and system reliability
• Improve testing, monitoring, observability, and documentation

Requirements:

• 5+ years of software engineering experience
• Strong backend development experience in Go or Python
• Hands-on machine learning experience using PyTorch, Scikit-learn, or similar frameworks
• Experience building end-to-end ML systems including feature pipelines, deployment, monitoring, and model iteration
• Strong SQL and database knowledge
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Excellent written and verbal English communication
• Experience in fraud detection, risk, cybersecurity, bot detection, device fingerprinting, or VPN/proxy detection
• Experience building low-latency ML systems for real-time predictions
• Familiarity with Docker, Kubernetes, CI/CD, and modern DevOps practices
• Experience using LLMs for automation