Machine Learning Engineer

AI Talent Hunt is seeking a Machine Learning Engineer to join their team full-time. The role involves engineering scalable ML systems for real-time fraud detection and requires collaboration across various engineering domains to ensure effective and secure solutions.

Responsibilities:

• Design and build machine learning systems for real-time fraud detection
• Work across machine learning, backend engineering, and data infrastructure
• Own end-to-end ML solutions from data processing to production deployment
• Build scalable, reliable, and efficient systems for high-stakes fraud prevention
• Build and optimize real-time data pipelines for device and behavioral data
• Develop, deploy, and maintain production ML models for fraud detection
• Engineer production-ready features from raw data
• Collaborate with backend and platform engineers to integrate ML systems
• Monitor model performance and iterate based on production feedback
• Maintain security, privacy, and compliance standards
• Follow best practices for testing, documentation, and observability

Requirements:

• 5–8 years of software engineering experience
• Strong backend engineering experience with Go or Python
• Hands-on experience building applied machine learning solutions using large datasets
• Experience owning end-to-end ML systems, including feature engineering and pipelines, model deployment, production monitoring, and continuous model improvement
• Experience building latency-sensitive ML systems serving real-time predictions at scale
• Strong backend engineering mindset with production system experience
• Experience in fraud detection, including areas such as bot detection, device fingerprinting, and VPN and proxy detection
• Go or Python
• PyTorch or Scikit-learn
• SQL
• Relational and NoSQL databases
• Feature pipelines
• Model monitoring and drift detection
• Docker
• Kubernetes
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Strong written and verbal English communication
• Self-directed and comfortable working with minimal supervision
• Able to navigate ambiguity and deliver independently
• Stronger backend engineering background than data science
• Experience with CI/CD pipelines
• Knowledge of browser APIs and high-entropy data collection techniques
• Experience using frontier LLMs for automation
• Ability to quickly learn new programming languages