Cisco - San Jose, CA

posted about 1 month ago

Full-time - Mid Level
San Jose, CA
Computer and Electronic Product Manufacturing

About the position

The Machine Learning Engineer for Security AI at Cisco Systems is responsible for developing and implementing advanced machine learning models and algorithms to address security challenges. This role focuses on creating innovative solutions that enhance threat detection, anomaly detection, and risk assessment, while ensuring model scalability and efficiency in production environments. The position requires a strong background in machine learning, particularly in customizing models for specific problems and handling high-dimensional data.

Responsibilities

  • Develop and implement advanced ML models and algorithms to tackle security problems, including threat detection, anomaly detection, and risk assessment.
  • Lead the training, validation, and fine-tuning of ML models using current techniques and libraries, defining and tracking security-specific metrics for model performance.
  • Build robust software systems to integrate, deploy, and maintain advanced ML models in production environments, optimizing software frameworks and ensuring high reliability.
  • Collaborate with software engineering teams to design and implement deployment strategies for models into security systems, ensuring scalability and efficiency.
  • Establish an effective process for machine learning and security operations, maintaining clear documentation of models, data pipelines, and security procedures.

Requirements

  • 3+ years' experience in programming languages such as Python or R, and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • 2+ years' experience building machine learning systems and scalable solutions.
  • BA / BS degree with 2+ years of experience (or) MS degree with 1+ years of experience as a machine learning engineer.

Nice-to-haves

  • Expertise in machine learning algorithms, deep learning, and statistical modeling.
  • Excellent problem-solving and communication skills, with the ability to explain complex concepts to non-technical teammates.

Benefits

  • Ongoing investment in employee growth through mentorship programs and learning resources.
  • Inclusive Communities employee resource groups to promote diversity and collaboration.
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