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Seeking an AI Engineer for a remote contract opportunity to collaborate with Cybersecurity and Machine Learning teams to identify and prioritize ML use cases in Cybersecurity. The role will design, develop and validate ML/LLM POCs using local development environments.

**PST or able to accommodate PST working hours

Responsibilities:

• Design, train, test, and optimize ML and LLM models to address specific cybersecurity challenges such as malware detection, phishing prevention, and anomaly detection.
• Provide guidance on model selections, feature engineering, and hyperparameter optimization to address Cybersecurity use cases.
• Lead the development of an in-house AI agent (similar to a co-pilot) designed to provide real-time insights, recommendations and automated responses to routine queries or incidents.
• Collaborate with data teams to preprocess, clean, and engineer features from large-scale cybersecurity datasets.
• Integrate ML models with existing Cybersecurity tools and workflows for automated threat detection, anomaly detection and risk scoring.
• Develop documentation and deliver knowledge transfer sessions to enable the Cybersecurity Operations team to manage and maintain the ML solutions.
• Stay updated with the latest ML/LLM trends, especially in the applications related to Cybersecurity and recommend innovative approaches.
• Assist in creating a framework for continuous monitoring and retraining of ML models to maintain performance over time.

Education/Experience 

• Bachelor’s or Master’s degree in Computer Science, Cybersecurity, Data Science, or a related field.
• 5+ relevant work experience similar roles.
• Certifications in relevant technologies or methodologies. 

Required Skills and Knowledge 

• Programming: Proficient in Python for data manipulation, feature engineering, and model development.
• Data Management and Feature Engineering: Strong knowledge of SQL for querying and preprocessing data. Collaborate with data teams to preprocess, clean, and engineer features from large-scale cybersecurity datasets.
• Model Development and Optimization: Design, train, test, and optimize ML and LLM models to address specific cybersecurity challenges such as malware detection, phishing prevention, and anomaly detection.
• Environment Management: Expertise in Miniconda for creating and managing development environment.
• ML/AI Tools: Experience with Azure ML Studio for deploying ML solutions.
• ML Framework: Familiarity with libraries such as TensorFlow, PyTorch, Scikit-learn, or similar.
• Cybersecurity Tools: Understanding of how ML can be applied to areas such as anomaly detection, intrusion detection, UEBA and risk assessment.
• Problem-solving mindset with a focus on delivering scalable and reliable solutions.
• Excellent project management skills.
• Excellent communication and collaboration skills to work effectively with cross-functional teams.
• Ability to translate complex ML concepts into actionable insights for non-technical stakeholders.