AI Specialist

at  KAISHI PARTNERS PTE LTD

ABOUT US:

We are a cybersecurity startup based in Singapore, specializing in the browser detection and response space. Our mission is to redefine how businesses secure their digital environments through cutting-edge technologies. Join our team and contribute to building AI-driven solutions that enhance cybersecurity defenses.

QUALIFICATIONS:

• Proven experience in training and fine-tuning Large Language Models (e.g., GPT, BERT).
• Strong understanding of anomaly detection techniques and their applications incybersecurity.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or similar.
• Experience working with large datasets and data preprocessing techniques.
• Familiarity with cybersecurity concepts, tools, and data types is highly desirable.
• Excellent problem-solving skills with the ability to work in a dynamic and fast-paced startup environment.
• Strong communication skills and the ability to collaborate effectively with cross-functional teams.
• Master’s or Ph.D. in Computer Science, AI/ML, Data Science, or a related field is preferred but not mandatory.

ROLE OVERVIEW:

We are looking for an AI Specialist to work on the development and training of advanced AI models, focusing on Large Language Models (LLMs) and anomaly detection systems. This role offers a unique opportunity to work at the intersection of AI and cybersecurity, creating solutions that proactively identify and mitigate threats.

KEY RESPONSIBILITIES:

• Design, develop, and train LLM models tailored to our cybersecurity use cases.
• Implement and enhance anomaly detection algorithms to identify unusual patterns and potential threats.
• Collaborate with the engineering and product teams to integrate AI models into our browser detection and response platform.
• Analyze large datasets to extract insights and improve the accuracy of detection mechanisms.
• Stay updated on advancements in AI/ML technologies and propose innovative solutions for our cybersecurity challenges.
• Optimize model performance, scalability, and deployment in real-world applications.
• Document research findings, methodologies, and results to share with the team and stakeholders.