Cisco
Principal Machine Learning Engineer
San Jose, California, US · Principal · Full-time
Sponsorship not specified$292k-$369kDetected 2 hours ago
Backend DevelopmentVector DatabasesMachine LearningData EngineeringLLMsRAGAgentic AIA/B TestingCybersecuritySIEMSOARSOC OperationsDetection EngineeringCiscoResearch
About the role
- The application window is expected to close on: 08/27/2026 Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.
- This is a place for builders who thrive in ambiguity, challenge the status quo, and care deeply about making a meaningful impact.
- If you're energized by tough problems, excited to shape the future of cyber defense, and eager to work alongside passionate experts, you'll feel right at home.
Responsibilities
- Design and build agentic workflows that combine detection signals, context, and playbooks to automate threat triage and response.
- Prototype and test new AI features-from enrichment agents to incident summarization-working closely with Security SMEs to validate real-world utility.
- Develop an AIOps pipeline to enable rapid experimentation with prompts, models, and RAG systems, using clear, measurable success criteria to evaluate iterations.
- Collaborate with Product and Platform teams to co-design AI-enhanced TDIR workflows that are intuitive, scalable, and immediately useful to analysts.
Requirements
- Bachelor's degree with 12+ years of related experience, Master's degree with 7+ years of related experience, or PhD with 5+ years of related experience.
- Experience with Security Operations concepts, including threat detection, triage, investigation, and incident response.
Nice to have
- Experience evaluating AI model performance using structured experimentation, including accuracy, reliability, usability, latency, and cost optimization.
- Experience designing evaluation frameworks and experiments for LLM-based applications.
- Experience with SIEM and SOAR platforms, such as Splunk, from a practitioner, engineering, or automation perspective.
- Experience as a Tier 3 SOC Analyst, Detection Engineer, Security Automation Engineer, or similar Security Operations role.
- Experience with LLM fine-tuning, embedding models, or domain-specific AI customization for cybersecurity applications.
- We work as a team, collaborating with empathy to make really big things happen on a global scale.
- Because our solutions are everywhere, our impact is everywhere.
- Message to applicants applying to work in the U.S. and/or Canada:
Compensation
- The starting salary range posted for this position is $291,500.00 to $369,100.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benef
Benefits
- Please see the Cisco careers site to discover more benefits and perks.
- Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.
- 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees
- 1 paid day off for employee's birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco
- Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees
- Exempt employees participate in Cisco's flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)
- 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next
- Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training.
This listing is sourced directly from Cisco's careers page and normalized into a canonical job model.