AI Researcher

About Plurall AI

Plurall AI specializes in AI-driven cybersecurity solutions aimed at combating fraud and deepfake threats. Leveraging a proprietary AI platform capable of near real-time analysis with nearly perfect accuracy, the company empowers organizations to swiftly identify and address digital threats. Their mission is to alleviate operational disruptions and concerns caused by sophisticated cyber attacks by offering proactive risk detection and mitigation strategies, enabling clients to focus on their primary business operations. Joining Plurall AI means contributing to innovations that enhance global business trust, security, and resilience.

Role Overview

The AI Researcher will be instrumental in creating, refining, and assessing machine learning and pattern recognition models crucial to Plurall AI's cybersecurity and fraud prevention technologies. Responsibilities include conducting both practical and theoretical research, prototyping new solutions, executing experiments, and scrutinizing performance data to advance the GaussMass AI system. Collaboration is key as the role interfaces with data engineering, product development, and cybersecurity experts to convert complex business needs into effective AI-driven solutions. Clear documentation and communication of results to diverse audiences are essential. The position is full-time based in New York City with a hybrid schedule combining on-site teamwork and remote work.

Qualifications

• Solid understanding of computer science fundamentals such as algorithms, data structures, and software engineering.
• Expertise in machine learning and pattern recognition with hands-on experience in model design and optimization for applied contexts.
• Proven background in data science research including designing experiments, evaluating models, and critically analyzing results.
• Strong statistical skills for modeling, hypothesis testing, and handling large-scale complex datasets.
• Competence with Python or equivalent programming languages and familiarity with ML libraries like PyTorch, TensorFlow, and scikit-learn.
• Experience or knowledge in cybersecurity, fraud detection, or deepfake identification domains is highly advantageous.
• Excellent ability to convey complex technical ideas clearly and collaborate with interdisciplinary teams.
• Advanced degree in computer science, data science, statistics or a related discipline preferred, though extensive relevant experience is acceptable.