Principal Machine Learning Engineer (AI/Cybersecurity)

TL;DR

Principal Machine Learning Engineer (AI/Cybersecurity): Leading the design and development of cutting-edge, production-ready AI/ML systems and pipelines for critical cybersecurity applications with an accent on agentic frameworks, threat detection, and anomaly detection. Focus on optimizing existing machine learning pipelines for scalability, exploring advanced AI techniques, and ensuring system reliability under complex security challenges.

Location: Hybrid role based in San Jose, CA, USA

Salary: $182,000 – $260,000 USD

Company

hirify.global is a global leader in zero trust security, pioneering advanced AI to combat billions of cyber threats and policy violations daily.

What you will do

• Lead the design and development of cutting-edge, production-ready AI/ML systems and pipelines for cybersecurity applications.
• Optimize existing machine learning pipelines for improved efficiency and scalability.
• Explore and experiment with advanced AI techniques and architectures to solve complex cybersecurity problems.
• Provide technical guidance to junior and mid-level engineers.
• Collaborate with cross-functional teams to define project requirements and ensure alignment with business objectives.
• Ensure systems and applications meet reliability, scalability, and performance requirements.

Requirements

• Bachelor's degree in Computer Science or a related technical field.
• 10+ years of experience as a Machine Learning Engineer or Scientist, with a proven track record of delivering successful projects in cybersecurity.
• Strong proficiency in Algorithms, Game Theory, Optimization, and ML libraries/frameworks.
• Extensive experience in data modeling, feature engineering, model development, and error analysis.
• Excellent communication skills with the ability to translate complex technical concepts.

Nice to have

• Proven track record of designing, building, and shipping end-to-end applications at scale.
• Familiarity with multi-agent systems and orchestration frameworks.
• Deep expertise with cloud infrastructure such as AWS or GCP for AI workloads.
• Strong experience with agent architectures and SOTA AI frameworks.
• Contributions to open-source ML projects or top-tier research publications.

Culture & Benefits

• Comprehensive health plans, time off plans for vacation and sick leave, and parental leave options.
• Retirement options and education reimbursement.
• In-office perks.
• Inclusive environment that values all backgrounds and perspectives.
• Culture of execution centered on customer obsession, collaboration, ownership, and accountability.
• Focus on impact, transparency, and constructive debate.