Machine Learning Engineer

GitHub, Inc. is hiring an experienced Machine Learning Engineer to design, build, and deploy agentic LLM-based solutions that help detect and prevent fraud, abuse, and security threats across GitHub at scale. The role also involves identifying vulnerabilities tied to abuse, performing ad-hoc analysis, and assessing the impact of safety and integrity initiatives.

Responsibilities

• Design, build, and deploy agentic solutions using large language models for large-scale detection and prevention of fraud, abuse, and security threats, including content classification and multi-step agentic investigations.
• Build production-grade systems that operate reliably against high-volume event streams, leveraging AI coding assistants to accelerate and improve development.
• Develop and operate scalable machine learning systems on cloud platforms, including Azure AI Foundry, to train, deploy, and serve models and agentic solutions in production.
• Evaluate and improve existing models and agentic solutions through offline evaluations, including tool-use loops and LLM-as-judge evaluation, along with performance metrics and feedback from operational deployments.
• Identify vulnerabilities in products that can lead to abuse and consult with product teams during reviews of new features.
• Collaborate 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 peers.

Requirements

• 4+ years of experience in machine learning or a related field; or a Bachelor’s degree in Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or a related field plus 2+ years of machine learning experience; or a Master’s degree in Machine Learning or related fields; or equivalent experience.
• Strong understanding of large language models, including hands-on experience applying them at scale, ideally for classification and agentic workflows or agents.
• Strong software engineering skills, including experience building with AI coding assistants.
• Experience designing or evaluating agentic systems, such as tool-use loops, multi-step workflows, or LLM-as-judge evaluation.
• Hands-on experience building and operating classification or detection systems at scale, including work with imbalanced data and precision/recall tradeoffs.
• Experience in Trust and Safety, National Security, or fighting spam, malware, fraud, and threat actor activity at scale.
• Experience in responsible AI and Safety-by-Design.
• Experience handling user data and privacy.
• Solid understanding of machine learning algorithms (supervised and unsupervised learning, anomaly detection, etc.) and practical implementation.

Technologies

• Large language models (LLMs)
• Azure AI Foundry
• Tool-use loops
• LLM-as-judge evaluation
• AI coding assistants
• Machine learning
• Precision/recall tradeoffs

What We Value

• Collaboration
• Empathy
• Quality
• Positive Impact
• Shipping

Compensation

The base salary range for this role is USD $107,700.00 to USD $285,900.00 per year.

Locations

• Remote (United States)

Leadership Principles

• GitHub values: Customer-obsessed, Ship to learn, Growth mindset, Own the outcome, Better together, Diverse and inclusive
• Manager fundamentals: Model, Coach, Care
• Leadership principles: Create clarity, Generate energy, Deliver success