Job
Description
As a Machine Learning Engineer at Cisco Security AI, your role will involve the following responsibilities and qualifications: **Role Overview:** You will be part of the Cisco Security AI team, working on AI products and platforms to enhance the cybersecurity industry. Your primary focus will be on developing and implementing machine learning solutions to address real-world problems and enhance security resilience using AI and Machine Learning technologies. **Key Responsibilities:** - Deep Knowledge of LLM Architecture: You should have a comprehensive understanding of large language models architecture, particularly Transformer-based models like GPT, and their variants. - Language Model Training and Fine-Tuning: Experience in training large-scale language models from scratch and fine-tuning pre-trained models for specific applications or domains. - Data Preprocessing for NLP: Skills in preprocessing textual data, including tokenization, stemming, lemmatization, and handling different text encodings. - Transfer Learning and Adaptation: Proficiency in applying transfer learning techniques to adapt existing LLMs to new languages, domains, or specific business needs. - Handling Ambiguity and Context in Text: Ability to design models that effectively handle ambiguities, nuances, and context in natural language processing. - Application of LLMs: Experience in applying LLM technology in areas such as chatbots, content creation, and semantic search. - Data Annotation and Evaluation: Skills in designing data annotation strategies for training LLMs and evaluating their performance using appropriate metrics. - Scalability and Deployment: Experience in scaling LLMs for production environments, ensuring efficiency and robustness in deployment. - Model Training, Optimization, and Evaluation: Complete cycle of training, fine-tuning, and validating language models for virtual assistants, chatbots, and content recommendation systems. - Algorithm Development for Enhanced Language Understanding: Develop or refine algorithms to improve the efficiency and accuracy of language models. - Applying LLMs to Cybersecurity: Tailor language models for cybersecurity purposes like threat intelligence analysis and automating responses to security incidents. - Deployment Strategy: Collaborate with software engineering teams to implement deployment strategies for machine learning models into security systems. - Documentation and Best Practices: Establish best practices for machine learning and security operations, and maintain clear documentation of models, data pipelines, and metrics. - Experimentation with Emerging Technologies and Methods: Explore new technologies and methodologies in language model development. - Mentoring and Cross-Functional Collaboration: Provide mentorship to team members and work collaboratively with cross-functional teams. **Qualifications Required:** - BA / BS degree with 7+ years of experience or MS degree with 5+ years of experience as a machine learning engineer. - Solid experience in machine learning engineering with a strong portfolio of successful projects. - Extensive experience in building machine learning systems and scalable solutions. - Expertise in machine learning algorithms, deep learning, and statistical modeling. - Preferred Qualifications: Advanced degree in Computer Science, Data Science, Statistics, Computational Linguistics, or related field. - Proficiency in programming languages like Python or R and experience with machine learning libraries such as TensorFlow, PyTorch, scikit-learn. - Excellent problem-solving and communication skills with the ability to explain complex concepts to non-technical stakeholders. - Proven ability to work collaboratively in cross-functional teams. Please note that the above mentioned details are specific to the job description provided by Cisco Security AI team for the position of Machine Learning Engineer.,
