Member of Technical Staff, Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI Security): Designing, training, and deploying ML-powered defenses for Copilot against threats like prompt injection, adversarial manipulation, and unsafe delegation with an accent on secure identity flows and privacy-first systems. Focus on building adaptive detection and policy models, developing AI security evaluation frameworks, and encoding security judgment into AI responses at a global scale.

Location: Hybrid in Mountain View, United States. Employees must live within a 50-mile commute of a designated Microsoft office in the U.S. and are expected to work from the office at least four days per week.

Salary: USD $158,400 – $258,000 per year (for San Francisco Bay Area, which includes Mountain View, and New York City metropolitan area).

Company

hirify.global is at the core of Microsoft’s mission to deliver trusted, human-centered AI experiences, making security and resilience intrinsic to every Copilot interaction.

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 rather than relying solely on static rules.
• Build and own evaluation frameworks for AI security, including adversarial testing, red-teaming support, and continuous robustness measurement.
• Partner with security and engineering teams to integrate ML defenses into secure orchestration frameworks.
• Apply ML to encode security “common sense” and 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 AND 4+ years technical engineering experience with coding in languages including 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.

Nice to have

• Master’s Degree in Computer Science or related technical field AND 6+ years or Bachelor’s Degree AND 8+ years technical engineering experience.
• 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.
• Exposure to distributed ML systems, large-scale data processing, or model serving in cloud environments.

Culture & Benefits

• Contribute to a culture of inclusion, respect, integrity, and accountability.
• Work on defining how AI systems develop and apply security judgment, enabling powerful new capabilities for users worldwide.
• Access to comprehensive benefits and compensation information via the Microsoft careers portal.
• Opportunity to establish best practices for secure agentic AI across Microsoft.