Machine Learning Engineer, Security AI

at  Cisco Systems

WHO WE ARE

The Cisco Security AI team delivers AI products and platform for all Cisco Secure products and portfolios so businesses around the world can defend against threats and safeguard the most vital aspects of their business with security resilience. We are passionate about making our customers secure by simplifying security with zero compromise using AI and Machine Learning.

BASIC QUALIFICATIONS

• Bachelors degree with 5+ years (or) Masters degree with 3+ years (or) PhD degree with 1+ year of software development industry experience
• 2+ years of industry experience in machine learning to include building, fine tuning and deploying machine learning models into production
• 2+ years of experience with machine learning libraries such as TensorFlow, PyTorch,or Skit-learn

PREFERRED QUALIFICATIONS

• Experience in machine learning algorithms, deep learning, and statistical modeling.
• Experience in NLP and LLMs
• Experience in GenAI
• Proficient in cloud services for deploying models at scale
• Excellent problem-solving and communication skills, with the ability to explain complex concepts to non-technical teammates.

In this role, you will tackle some of the most challenging issues facing businesses today. You will do this through:
Model Development: Develop and implement advanced ML models and algorithms to tackle security problems, including threat detection, anomaly detection, and risk assessment.
Model Training and Evaluation: Lead the training, validation, and fine-tuning ML models using current techniques and libraries. Define and track security-specific metrics for model performance.
Solution Development: Build robust software systems to integrate, deploy, and maintain advanced ML models in production environments.
Deployment Strategy: Collaborate with software engineering teams to design and implement deployment strategies for models into security systems, ensuring scalability, reliability, and efficiency.
Documentation and Best Practices: Establish an effective process for machine learning and security operations, and maintain clear documentation of models, data pipelines, and security procedures.