Machine Learning Engineer.

4 weeks ago

San Jose, United States Cisco Full time

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.

Who You Are

You are a passionate software engineer with a proven track record of successfully developing and implementing models that address real-world problems. You will be proficient in the following areas:

Problem-Specific Model Customization: Experience adapting 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 managing and extracting useful patterns from high-dimensional data spaces, using techniques like dimensionality reduction or specialized network architectures.

Proficiency in NLP and LLM: Including experience with BERT, GPT, or similar, to effectively 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 knowledge (from cybersecurity or other domains) and out-of-the-box thinking.

Model Scalability and Efficiency: Expertise in developing 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

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. 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 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.

Basic Qualifications

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.

Preferred Qualifications

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.

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