Job
Description
AI/ML Engineer LLM PII Detection Department: Data Science / AI Engineering Role Overview We are seeking a skilled AI/ML Engineer to join our team focused on building and fine-tuning local LLM models for PII detection at scale (50+ PB of data). In this role, you will work closely with our AI Expert (Team Lead) to develop, deploy, and optimize state-of-the-art AI models that can detect Personally Identifiable Information (PII) across diverse data sources—including documents, databases, knowledge graphs, code, and more. Key Responsibilities Model Development: Assist in designing, training, and fine-tuning local LLM models for PII detection. Develop generative AI agents that utilize data schema and metadata to enhance PII detection process - reducing workload sizes with smart sampling. Framework Implementation: Utilize frameworks such as Ray, llama.cpp, ollama, vLLM, and PyTorch to build and scale AI models. Implement and support distributed computing frameworks to process and analyze large-scale datasets efficiently. Deployment & Optimization: Support the deployment of AI/ML solutions on both Azure and on-premise infrastructures. Monitor model performance, troubleshoot issues, and iterate to ensure optimal performance with evolving data. Collaboration: Work collaboratively with cross-functional teams—including data engineering, security, and compliance—to align AI solutions with business needs. Participate in code reviews, share insights, and document best practices to maintain high standards across projects. Continuous Improvement: Engage in ongoing learning and development of new AI methodologies. Contribute to the enhancement of model robustness and scalability, ensuring our systems handle 50+ PB of data reliably. Technical Proficiency: Hands-on experience with Python and ML frameworks (especially PyTorch). Familiarity with distributed computing tools such as Ray/Pyspark. Experience with LLM frameworks/tools such as llama.cpp, ollama, and vLLM. Data Handling: Ability to work with very large datasets and implement scalable, distributed solutions. Prior exposure to AI model development and fine-tuning for specialized tasks. Deployment Expertise: Experience deploying AI/ML models on Azure cloud platforms and/or on-premise environments. Communication & Collaboration: Strong communication skills to effectively collaborate with team members and cross-functional stakeholders. A proactive approach to problem-solving and a commitment to quality. Experience in PII detection, data privacy projects, or related fields. Basic understanding of data security and compliance frameworks. Familiarity with generative AI techniques and prompt engineering. Previous exposure to the fintech, payments, or security domains is a plus.
