Machine Learning Engineer

GitHub is the world’s leading platform for agentic software development, and they are seeking an experienced machine learning engineer to help design, build and deploy agentic solutions. The role involves identifying trends related to safety, fraud, and abuse on GitHub and collaborating with cross-functional teams to ensure the platform's security and integrity.

Responsibilities:

• Design, build and deploy agentic solutions that leverage large language models to detect and prevent fraud, abuse, and security threats at scale — applying LLMs to problems such as content classification and multi-step agentic investigation
• Build well-engineered, production-grade systems that run reliably against high-volume event streams, making effective use of AI coding assistants to accelerate and improve your work
• Build and operate scalable ML systems on cloud platforms (such as Azure AI Foundry) for training, deploying, and serving models and agentic solutions in production
• Evaluate and improve existing models and agentic solutions using offline evaluations (including tool-use loops and LLM-as-judge evaluation), performance metrics, and feedback from operational deployments
• Identify vulnerabilities in products that lead to abuse, and provide consultation to product teams reviewing new features
• Collaborate closely with cross-functional teams including data scientists, software engineers, product managers and content moderators to integrate agentic solutions into production systems
• Document the systems you help build and support the technical growth of your peers