Machine Learning Engineer

• Develop scalable backend services and microservices in Java or Go to support ML-driven orchestration.
• Build and optimize data pipelines and infrastructure to support event-driven, async, and long-running ML processes.
• Partner with engineering teams to automate workflows, integrate models, and ensure revenue protection.
• Educate internal stakeholders on ML-driven decision-making and create transparent, traceable systems for fraud management.
• Drive automation and orchestration of workflows across fraud, billing, and manual operations teams.
• Leverage AI-assisted development tools (e.g., GitHub Copilot, ChatGPT) to accelerate prototyping, code generation, debugging, and documentation.
• Evaluate and integrate AI-powered solutions into workflows to improve productivity, model experimentation, and system efficiency.
• Collaborate within a small cross-functional team (PM, ML Engineer, BE Engineer) while contributing to the larger AI & Data org.
• Champion best practices in software engineering, code quality, testing, and deployment of ML/LLM solutions.
• Design, build, and deploy machine learning models and large language model (LLM) applications in production environments.
• Strong collaboration and communication skills, with the ability to explain technical concepts to diverse stakeholders.

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