AI Researcher / ML,Gen AI, LLM, Lead ML Teams AI Assistant

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.