AI/ML Agentic Systems Developer (Threat Analysis)

We are seeking a highly motivated and experienced AI/ML Systems Developer to be a key contributor to our top-notch team. You will be instrumental in developing a cutting-edge AI solution for automated malware analysis and threat intelligence (CTI). This is a unique opportunity to combine deep expertise in machine learning, low-level systems, and high-performance development to build high-impact, defensive technologies from the ground up.

Key Responsibilities

As an AI/ML Systems Developer, your primary focus will be on leveraging technology to automate and enhance malware analysis and CTI:

• Design, develop, and deploy end-to-end solutions for automated malware analysis and threat detection using Machine Learning (ML), with a focus on Large Language Models (LLMs) and agentic workflows.
• Integrate your low-level proficiency and Reverse Engineering skills (including static analysis, tools like IDA,, etc.) in groundbreaking research.
• End-to-end engineering capabilities by prototyping solutions and taking full-stack ownership of components, from data ingestion and model training to deployment and integration into CTI platforms.
• Conducting deep-dive Malware Analysis, developing and deploying automated detection mechanisms like YARA rules, processing large volumes of IOCs (Indicators of Compromise), and managing extensive sample databases and telemetry sources.
• Employ strong analytical skills and systems thinking to tackle complex, novel AI challenges in the realm of threat detection and intelligence.
  
  

• 5+ years of experience in software engineering, machine learning, or a related technical role, or a shorter tenure coupled with exceptional technical depth.
• Strong professional experience with Rust and Python.
• Broad working familiarity with modern infrastructure and architecture topics, including Linux/Unix environments, networking, cloud platforms, observability, various datastores, and containers.
• Proven experience in ML engineering, particularly in designing and deploying models (LLMs, Deep Learning, etc.) in a production environment, specifically applied to security data analysis (e.g., binary analysis, network traffic, CTI feeds).
• Deep understanding and practical experience in Reverse Engineering and low-level systems analysis for feature extraction from suspicious samples.
• Hands-on experience with malware analysis, including the creation and maintenance of detection signatures (e.g., YARA) and integrating with CTI systems.
• A self-driven problem-solver with a passion for tackling unstructured challenges and an aptitude for systems thinking.