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Cisco Engineering Leader Machine Learning 
United States, California, San Jose 
516375681

12.06.2024

Who You Are

You are an accomplished innovator with a track record of leading teams and architecting machine learning solutions that have made a significant impact. You are deeply passionate about ML, and you thrive in a leadership role where you can mentor and inspire others. Your ideal attributes include:

  • Technical Leader: As a leader who coaches, teaches and mentors teams of ML engineers and data scientists, you drive them toward excellence in research, development, and solution deployment.
  • Architectural Vision: You possess a deep understanding of ML systems architecture, and you can design complex, scalable, and reliable solutions that meet security and performance requirements.
  • Problem-Specific Model Customization: Ability to use and adapt neural network architectures like GANs (Generative Adversarial Networks), Autoencoders, Attention Mechanisms, and Transformers or developing novel architectures to address unique challenges in different domains (e.g., NLP, computer vision, time series analysis).
  • Handling High-Dimensional Data: Experience in extracting useful patterns from high-dimensional data spaces, applying techniques like dimensionality reduction or specialized network architectures.
  • Proficiency in NLP and LLM is beneficial, including experience with BERT, GPT, or similar, to derive insights from structured and/or unstructured text data. Building custom real-world production NLP models for tasks like text generation or text summarization is a strong plus.
  • Innovative Solution Development: Ability to apply deep learning techniques innovatively to solve complex, problems, often combining domain expertise (from cybersecurity or other domains) and out-of-the-box thinking.
  • Model Scalability and Efficiency: Expertise in developing scalable and efficient models that can be deployed in different environments, including understanding trade-offs between model complexity and performance.
  • Continuous Learning and Adaptation: Commitment to staying abreast of the latest research and trends in deep learning, continually integrating new findings and techniques into problem-solving approaches.

What You Will Do

  • Lead and mentor an engineering team, providing technical guidance, setting strategic direction, and fostering a culture of innovation and excellence.
  • Architecture Design:Design and architect complex ML systems, ensuring alignment with the overall security strategy.
  • Model Development:Develop and implement innovative ML models and algorithms to solve complicated security problems, including threat detection, anomaly detection, and risk assessment.
  • Model Training and Evaluation:Deliver the training, validation, and fine-tuning of ML models, using innovative techniques and libraries. Define and document security-specific metrics for model performance.
  • Solution Development:Design, build and implement robust software systems to integrate, deploy, and maintain ML models in production environments. This includes developing and optimizing software frameworks, ensuring seamless model integration, and rigorously testing systems to maintain high reliability and performance standards.
  • Deployment Strategy:Collaborate with engineering teams to design and implement deployment strategies for machine learning models into security systems, ensuring scalability, reliability, and efficiency.
  • Documentation and Best Practices:Establish standard processes and maintain clear documentation of models, data pipelines, and security procedures.


Basic Qualifications

  • BA / BS degree with 15+ years experience or MS degree with 12+ years experience or equivalent experience
  • 7+ years developing machine learning systems, deploying them into production and building scalable solutions
  • 7+ years in machine learning algorithms, deep learning, and statistical modeling
  • 4+ years leading software engineering teams

Preferred Qualifications

  • Experience in productizing generative and non-generative AI solutions
  • Proficiency in programming languages such as Python or R, and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Excellent problem-solving and interpersonal skills, with the ability to explain complicated concepts to non-technical key stakeholders
  • Ability to work collaboratively in multi-functional teams.