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Tier-1 brand, metro location, mid-level experience, and multi-skill requirements drive high applicant competition.
Specialized AI security and LLM expertise strongly limits cross-industry transferability.
Explicit 3–5 years, mandatory LLM fine-tuning experience, and fixed tech stack make shortlisting highly selective.
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Assess security and robustness of AI networks against cyber attacks such as adversarial and data poisoning attacks.
Design and propose innovative security solutions to enhance AI implementation safety.
Develop and implement AI security projects independently using PyTorch, collaborating closely with cybersecurity and R&D teams.
Bachelor's degree in computer science engineering with dedicated AI coursework.
3 to 5 years total experience with minimum 1 year full-time experience fine-tuning LLM models or applying LLM to code vulnerability scanning, or equivalent AI domain experience linked to CDI activities.
Proven experience in cybersecurity of AI or advanced AI usage for security in previous projects.
Mandatory technical skills: Python, PyTorch, C, Java, Unix commands and scripting; strong knowledge of AI network architectures, implementation, linear algebra, and computer arithmetic; very good English communication skills.
Experience with LLM/transformer architectures including fine-tuning and customization methods, indicating a strong AI technical background.
Ability to work independently on AI security projects with research appetite for evolving AI security domain.
Comfortable interfacing and collaborating with cross-functional cybersecurity and R&D teams within a corporate engineering environment.