Member of Technical Staff – Machine Learning Engineer (AI Security)

TL;DR

Senior Machine Learning Engineer (AI Security): Designing, training, evaluating, and shipping ML-powered defenses for Copilot users with an accent on prompt injection, adversarial manipulation, and agentic workflow abuse. Focus on building adaptive detection and policy models, defining AI security judgment, and integrating ML defenses into secure orchestration frameworks.

Location: Redmond, United States. Starting January 26, 2026, employees who live within a 50-mile commute of a designated Microsoft office in the U.S. are expected to work from the office at least four days per week.

Salary: USD $119,800 – $234,700 per year (U.S. typical base pay)

Company

hirify.global is at the core of Microsoft’s mission to deliver trusted, human-centered AI experiences, focusing on security and resilience across Copilot interactions.

What you will do

• Design, train, and deploy ML-based defenses for threats such as prompt injection, adversarial inputs, and abuse of agentic workflows.
• Develop adaptive detection and policy models that learn from evolving attacker behavior.
• Build and own evaluation frameworks for AI security, including adversarial testing and red-teaming support.
• Partner with security and engineering teams to integrate ML defenses into secure orchestration frameworks.
• Apply ML to encode security judgment into AI responses, balancing usefulness, safety, and user intent.
• Monitor and analyze telemetry to improve model performance and guide iterative defense improvements.

Requirements

• Bachelor’s Degree in Computer Science or related technical field.
• 4+ years of technical engineering experience with coding in C, C++, C#, Java, JavaScript, or Python.
• 4+ years of hands-on experience building and shipping machine learning systems in production.
• Solid foundation in ML fundamentals, including classification, anomaly detection, representation learning, and model evaluation.
• Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow).
• Experience designing end-to-end ML pipelines: data collection, training, evaluation, deployment, and monitoring.
• Ability to reason about adversarial behavior, threat models, and failure modes in AI/ML systems.
• Experience working on AI safety, trust, or security-adjacent ML problems, including prompt injection, abuse detection, or adversarial ML.
• Familiarity with agentic or LLM-based systems, including tool calling, multi-step reasoning, or orchestration flows.
• Experience building ML evaluation and observability systems for real-world AI behavior.

Culture & Benefits

• Empower every person and organization on the planet to achieve more.
• Work in a culture of inclusion built on values of respect, integrity, and accountability.
• Eligible for comprehensive benefits and additional compensation programs.