Principal Machine Learning Engineer

Cisco Systems, Inc.•San Jose, CA

28d

About The Position

We are an agile team with a startup feel and a strong bias for action. We move fast, embrace failure as part of the process, and stay focused on solving real-world problems for defenders on the front lines. Our team blends deep expertise in AI, cybersecurity, and platform engineering. We are driven by a shared belief that the only way to outpace hackers is through AI advancements that free up humans to tackle real threats and more challenging problems. 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.

Requirements

Security Operations Experience - Understanding of security operations concepts, including detection, triage, investigation, and response.
Security Telemetry Fluency - Comfortable working with common data sources such as endpoint logs, network traffic, authentication events, or cloud audit trails-and understanding how they're used in detection and investigation workflows.
Senior-Level Python Development - Consistent record building scalable backend services, APIs, and automation workflows in Python.
DevOps/SecOps Practices - Proficient with CI/CD pipelines, version control (GitHub/GitLab), Jira, and automated testing frameworks.
Security Automation - Experience building and integrating with product APIs to drive SecOps efficiency.
Cross-Functional Collaboration - Comfortable partnering with product managers, security SMEs, and engineers to iterate quickly and deliver impactful solutions.
Prompt Engineering & LLM Integration - Skilled in crafting, testing, and optimizing prompts for large language models. Ideally, you have contributed to or shipped an AI-powered feature or product, and understand the nuances of integrating LLMs into real-world workflows-including usability, performance, and trust considerations.
AI Evaluation & Experimentation - Capable of designing experiments to evaluate LLM output for accuracy, usability, performance, and cost

Nice To Haves

SOAR/SIEM Familiarity - Experience working with security data and/or tools such as SIEM/SOAR platforms (e.g., Splunk), whether from a practitioner, developer, or automation perspective.
Splunk Enterprise Security (ES) Experience - Familiarity with ES architecture, correlation searches, notables, and risk-based alerting. Bonus if you've worked with Splunk's APIs, internals, or have experience developing on the Splunk platform.
Security Operations Background - Former Tier 3 SOC analyst or equivalent, with experience automating SecOps workflows and building scalable, resilient detection infrastructure.
RAG and Vector Search Implementation - Hands-on experience developing retrieval-augmented generation pipelines and working with vector databases (e.g., FAISS, Pinecone).
LLM Fine-Tuning and Embeddings - Exposure to fine-tuning large language models or generating custom embeddings for domain-specific tasks in cybersecurity.
Security Data Engineering - Experience building and maintaining pipelines for ingesting, parsing, and normalizing large-scale security telemetry.
UX and Human Factors for Analysts - Background or interest in designing intuitive, AI-assisted analyst workflows with a focus on usability, trust, and decision support.

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.
Evaluate model outputs for accuracy, reliability, and usability, then prototype and deploy improvements based on structured feedback and testing.
Collaborate with product and platform teams to co-design AI-enhanced TDIR workflows that are intuitive, scalable, and immediately useful to analysts.
Contribute to the core architecture powering AI-native security operations, helping to shape how Splunk and Cisco scale trusted automation across the enterprise.

Benefits

U.S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance.
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
Additional paid time away may be requested to deal with critical or emergency issues for family members
Optional 10 paid days per full calendar year to volunteer
For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco's policies.