Security Threat Detection Engineer Jobs

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Machine Learning Engineer

GitHub, Inc. Remote 📍 United States Remote

Remote

Today

$108k - $286k/yr Full time Agentic Ai Ai Enabled Security Ai Security

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Job Description

GitHub, Inc. is seeking an experienced Machine Learning Engineer to design, build, and deploy agentic LLM-based solutions that help detect and prevent fraud, abuse, and security threats on GitHub at scale. This role also focuses on identifying vulnerabilities that enable abuse, performing ad-hoc analysis, and measuring the real-world impact of safety and integrity efforts.

Responsibilities

Design, build, and deploy agentic solutions that use large language models to detect and prevent fraud, abuse, and security threats at scale, including applications such as content classification and multi-step agentic investigation.
Build production-grade systems that run reliably against high-volume event streams, leveraging AI coding assistants to accelerate and improve engineering work.
Build and operate scalable ML systems on cloud platforms, including 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 consult with product teams when reviewing new features.
Collaborate with cross-functional partners such as data scientists, software engineers, product managers, and content moderators to integrate agentic solutions into production systems.
Document the systems you build and support the technical growth of peers.

Requirements

4+ years 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 experience in machine learning, or a related field.
OR a Master's Degree in Machine Learning, Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or a related field.
OR equivalent experience.
Strong understanding of large language models, including hands-on experience applying them at scale for classification, 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 experience 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 managing 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: the best work is done together.
Empathy: putting people first.
Quality: setting the standard for excellence.
Positive Impact: making the world a better place through the work.
Shipping: creating things for the people using them.

Compensation

The base salary range for this job is USD $107,700.00 - USD $285,900.00 /Yr.

Locations

Remote (United States)

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