ML Developer with Cybersecurity

The ML/LLM Developer will be responsible for designing, developing, and maintaining advanced machine learning and large language model solutions for network security initiatives. Your role will involve strong expertise in NLP, deep learning frameworks, and fine-tuning LLMs. You will collaborate closely with the Data Scientist Lead and Data Engineer to ensure seamless integration into production systems. Your key responsibilities will include developing and maintaining machine learning and LLM-based solutions for network security, implementing and optimizing Retrieval-Augmented Generation (RAG) systems, designing prompt engineering strategies for diverse use cases, applying clustering algorithms and other ML techniques for threat detection and analysis, collaborating with cross-functional teams to enhance model accuracy and efficiency, as well as researching and integrating the latest advancements in ML and LLM technologies. To qualify for this role, you should possess a Bachelors or Masters degree in Computer Science, Software Engineering, or a related field, along with 3-5 years of experience in machine learning development focusing on NLP and LLMs. Proficiency in Python programming, expertise in deep learning frameworks such as TensorFlow and PyTorch, hands-on experience with Hugging Face Transformers and other LLM tools, as well as the ability to implement and fine-tune large language models are essential. Knowledge of RAG systems, vector databases like Faiss and Pinecone, experience with NLP libraries such as NLTK and spaCy, understanding of scaling ML workloads, and proven expertise in ML/LLM fine-tuning techniques are also required. Nice to have skills include familiarity with privacy-preserving machine learning techniques, experience with explainable AI methods, and exposure to deploying ML models in production environments.,