AI Researcher / ML,Gen AI, LLM, Lead ML teams AI Assistants and AI Agents / 13 years | Bangalore

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 defend against threats and safeguard the most vital aspects of business with security resilience. We are passionate about making businesses secure and simplify security with zero compromise using AI and Machine Learning. We are dedicated to harnessing data both at rest and in streaming, to drive innovation and empower organizations to make informed decisions.

Who You Are

You are someone with:

•Deep Knowledge of LLM Architecture: Comprehensive understanding of the architecture underlying large language models, such as Transformer-based models, including GPT (Generative Pre-trained Transformer), and their variants.

• Language Model Training and Fine-Tuning: Experience in training large-scale language models from scratch, as well as 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 of different text encoding.
• 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 NLP.
• Innovative Application of LLMs: Experience in creatively applying LLM technology in diverse areas such as chatbots, content creation, semantic search, and more.
• Data Annotation and Evaluation: Skills in designing and implementing 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.

What You Will Do

• Model Training, Optimization, and Evaluation: This encompasses the complete cycle of training, fine-tuning, and validating language models. You will be designing and adapting LLMs for use in virtual assistants, automated chatbots, content recommendation systems, etc.
• Algorithm Development for Enhanced Language Understanding: Focusing on the development or refinement of algorithms to improve the efficiency and accuracy of language models and understanding and generation tasks.
• Applying LLMs to Cybersecurity: Tailoring language models for cybersecurity purposes, such as analyzing threat intelligence, detecting cyber threats, and automating responses to security incidents.
• Experimentation with Emerging Technologies and Methods: Actively exploring new technologies and methodologies in language model development, including experimental frameworks and software tools.
• Mentoring and Collaboration: Providing mentorship to team members and working collaboratively with disparate teams to ensure cohesive development and implementation of language model projects.

Basic Qualifications

• Python
• 4+ years’ experience in natural language processing tools, including some of the following:
  • large language models, Gen AI & ML (Exp in leading small teams)
  • text classification
  • sentiment analysis
  • natural language generation
  
  
• BA / BS degree with 8+ years' experience (or) MS degree with 6+ years of experience (or) PHD + 3 years as a machine learning engineer or researcher.

Preferred Qualifications

• A thorough understanding of machine learning, particularly deep learning techniques, including knowledge of neural network architectures, training methods, and optimization algorithms.
• Knowledge and practical experience in NLP techniques and tools, including working with language models, text classification, sentiment analysis and natural language generation.
• Experience with frameworks including TensorFlow, PyTorch, or Keras.
• Skills in data preprocessing, cleaning, and analysis, with the ability to work with large datasets and extract meaningful insights.
• A background in conducting research, designing experiments, publishing papers, and keeping current with the latest advancements in LLMs.
• The capacity to think critically and tackle complex, innovative problems in the field.
• A willingness to continuously learn and adapt, crucial in the ever-evolving field of AI.