Why it's worth it Join ReliaQuest, a global leader in enterprise cybersecurity technology, where you'll be at the forefront of developing cutting-edge AI and ML solutions for our GreyMatter platform. You'll work with state-of-the-art technologies including: - Large Language Models (LLMs) and Generative AI - Autonomous AI Agents for security operations - Knowledge Graphs for enhanced threat detection - Cloud-native architecture and advanced ML systems We're not just following AI trends - we're setting them. Our GreyMatter platform combines traditional ML with next-generation AI capabilities to revolutionize security operations. The everyday hustle As a Data Scientist at ReliaQuest, you'll be: - Developing and implementing advanced machine learning models, with a special focus on LLMs and GenAI - Working on autonomous AI agents that enhance our security operations capabilities - Integrate AI agents with traditional ML systems - Creating and maintaining knowledge graphs for improved threat detection and response - Collaborating with cross-functional teams to integrate AI/ML solutions into our GreyMatter platform - Analyzing complex security data to identify patterns and anomalies - Participating in the full ML lifecycle from research to production deployment Do you have what it takes? Graduate Level - Master's degree in Statistics, Mathematics, Computer Science, Data Science, or related field - Strong programming skills in Python - Basic understanding of machine learning concepts and deep learning frameworks - Familiarity with NLP concepts and transformer architectures - Experience with basic data analysis and visualization - Eagerness to learn about LLMs and GenAI applications Mid Level - 3-5 years of experience in applied data science - Strong experience with machine learning model development and deployment - Hands-on experience with deep learning frameworks and LLMs - Experience with cloud computing platforms (AWS/Azure/GCP) - Track record of successfully deployed ML models in production - Understanding of AI/ML security considerations Senior Level - 6+ years of experience in data science with focus on production ML systems - Extensive experience training and deploying LLMs and GenAI solutions - Proven track record of leading complex AI/ML projects - Experience integrating AI agents with traditional ML systems - Expertise in knowledge graph technologies and applications - Strong background in production ML architecture and MLOps - Experience mentoring junior data scientists What makes you uncommon? Graduate Level - Previous experience with ML/AI projects - Contributions to open-source ML projects - Experience with basic LLM fine-tuning - Familiarity with graph databases - Knowledge of cybersecurity concepts Mid Level - Experience with LLM fine-tuning and prompt engineering - Knowledge of graph databases and knowledge graph construction - Experience with ML model monitoring and maintenance - Understanding of AI agents and their applications - Background in cybersecurity or security analytics Senior Level - Deep expertise in LLM architectures and training methodologies - Experience building and deploying autonomous AI agents - Advanced knowledge graph development and implementation experience - Expertise in combining traditional ML with GenAI solutions - Track record of innovative AI/ML solutions in production - Experience with large-scale ML systems architecture - Research publications or patents in ML/AI