Security Threat Detection Developer 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 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 at scale.

Responsibilities

Design, build, and deploy agentic LLM solutions for fraud, abuse, and security threat detection and prevention, including uses such as content classification and multi-step agentic investigations.
Develop production-grade systems that run reliably with high-volume event streams, leveraging AI coding assistants to accelerate and improve engineering output.
Build and operate scalable ML systems on cloud platforms (for example, Azure AI Foundry) to train, deploy, and serve models and agentic solutions in production.
Evaluate and improve models and agentic systems using offline evaluations, including tool-use loops and LLM-as-judge evaluation, plus performance metrics and feedback from production deployments.
Identify product vulnerabilities that enable abuse and provide consultation to product teams on reviewing new features.
Collaborate with cross-functional partners, including 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 and hands-on experience applying them at scale, ideally 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 handling 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 with responsible AI and Safety-by-Design.
Experience managing user data and privacy.
Solid understanding of machine learning algorithms (including supervised and unsupervised learning and anomaly detection) 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

Base salary range: USD 107,700.00 - USD 285,900.00 per year

GitHub 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

Location

Remote (United States)

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