1 month ago
Bengaluru, IndiaSenior
Responsibilities
- Develop and maintain static analysis capabilities for PE files, Authenticode signatures, YARA scans, Office macros, PDFs, archives, and cloud hash reputation lookups.
- Manage machine learning model integration, tuning, deployment, version control, feature engineering, and optimization in production inference services.
- Own Windows sandbox and dynamic analysis capabilities, including KVM/libvirt VM lifecycle management, guest configuration, behavioral telemetry, and additional operating system support.
- Read, debug, build, and modify C/C++ compiled analysis components.
- Develop new analysis engines, expand file-type coverage, create behavioral signatures, and improve detection workflow test coverage.
- Investigate and resolve false positives, false negatives, engine failures, and sandbox-related production issues.
- Participate in architecture, design, and code reviews and collaborate on platform performance, reliability, and detection accuracy.
- Provide maintenance-level support and first-line incident response for Python services, distributed task processing systems, management APIs, and deployment infrastructure.
Requirements
- At least 8 years of software engineering experience with a bachelor’s degree, 6+ years with a master’s degree, 3+ years with a PhD, or equivalent professional experience.
- Strong Python development skills, including multithreaded programming and performance optimization.
- Working proficiency in C and C++, including the ability to read, debug, build, and modify compiled components.
- Knowledge of static file analysis, PE structures, code-signing validation, YARA rules, Office macros, PDF formats, and archive inspection.
- Experience deploying and maintaining production machine learning inference solutions using technologies such as PyTorch, LightGBM, scikit-learn, or ONNX.
- Familiarity with KVM/libvirt or similar virtualization technologies and Windows internals, or the ability to develop expertise in these areas.
- Experience with malware analysis, sandbox technologies, threat detection platforms, or cybersecurity software.
- Comfort working in Linux environments, including process troubleshooting, log analysis, and shell scripting on Ubuntu or Debian-based systems.
- Strong written communication and effective collaboration skills in a distributed, asynchronous team environment.
Benefits
- Hybrid work arrangement.
- Equal opportunity employment in a diverse, international organization.
