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Specialized security and ML skills reduce applicants despite metro location and generic senior engineer title.
Highly domain-specific malware analysis, Windows internals, and sandboxing limit industry transferability.
Explicit 8+ years requirement plus mandatory Python, C/C++, malware analysis and virtualization skills make screening strict.
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Own and develop core detection capabilities including static and dynamic malware analysis engines, machine learning inference pipelines, and Windows sandbox environments.
Drive detection accuracy, platform reliability, and evolve analysis technologies for threat verdict generation.
Develop and maintain cloud-based scalable services for analyzing and classifying suspicious files using static, dynamic, and machine learning techniques.
Minimum 8 years software engineering experience with Bachelor's degree; or 6+ years with Master's, or 3+ years with PhD, or equivalent.
Strong Python development skills including multithreading and performance optimization.
Proficient in C and C++ for reading, debugging, and modifying compiled analysis components.
Experience with static file analysis (PE, Authenticode, YARA, Office macros, PDF, archive analysis), machine learning inference deployment (PyTorch, LightGBM, scikit-learn, ONNX), and virtualization technologies (KVM/libvirt).
Experienced in cybersecurity or threat detection platforms with expertise in malware analysis and sandbox technology.
Technical contributor comfortable with multi-language codebases (Python, C/C++) and virtualization setup for Windows environments.
Able to work effectively in distributed teams supporting multiple cross-functional technical areas including operational support and incident response.