Job Details

Metalware is a startup dedicated to protecting cyber-physical systems in critical industries. We develop advanced firmware security solutions for industries where failure isn't an option—ranging from aerospace/defense, automotive, and industrial controls to telecom and healthcare.

We are seeking an AI Research Engineer who will drive the development of intelligent models and algorithms to improve firmware security analysis. This role involves research and engineering at the intersection of artificial intelligence and cybersecurity, with a focus on creating systems that understand, diagnose, and predict vulnerabilities in embedded software.

WHO YOU ARE

• You possess a deep understanding of machine learning, deep learning, and natural language processing, and are eager to apply these skills to solve real-world security challenges.
• You enjoy engaging directly with cutting-edge customers—from drone and electric vehicle manufacturers to humanoid robot, nuclear reactor, and satellite companies—to understand their challenges and deliver rapid, effective solutions.
• You're comfortable gathering user feedback, understanding requirements, and quickly shipping code.
• You want to work side-by-side with the founders to shape product direction and technical roadmap.
• You're passionate about developing high-quality embedded software and own every aspect of the development lifecycle—from design and coding to testing and ongoing support.

RESPONSIBILITIES

• Design and implement machine learning architectures that can interpret binary data, facilitating automated symbolic recovery and analysis of stripped firmware images.
• Curate specialized datasets, customize model training processes, and deploy AI solutions into production environments.
• Research and develop deep learning models that identify patterns and anomalies indicative of vulnerabilities, enabling proactive security assessments.
• Create AI-driven frameworks that simulate potential attack scenarios by generating plausible exploit vectors based on detected firmware weaknesses.
• Develop algorithms to automatically trace the origins of firmware vulnerabilities, providing actionable insights for remediation.
• Participate in architecture, design, and code reviews to ensure robust and scalable solutions.
• Develop prototypes to validate key design concepts and quantify technical constraints.

MINIMUM QUALIFICATIONS

• Proficient Python, C, C++, or Rust, with a strong background in machine learning frameworks (e.g., TensorFlow, PyTorch).
• Demonstrated experience in designing and deploying machine learning models in production environments.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related STEM discipline with 3+ years of professional research or engineering experience; OR 5+ years of professional experience in lieu of a degree.

IDEAL QUALIFICATIONS

• Proven track record of research in machine learning, deep learning, or natural language processing applied to security or systems analysis.
• Familiarity with firmware architecture, reverse engineering, or binary analysis.
• Experience with transformer-based models or large language models (LLMs) for pattern recognition and automated reasoning tasks.
• A solid foundation in algorithms, data structures, and systems programming, with an emphasis on low-level software analysis.
• Prior experience in device product security and reverse engineering.
• Strong skills in debugging, performance optimization, and testing methodologies.

ADDITIONAL REQUIREMENTS

• Must be willing to work extended hours and weekends as needed to meet project deadlines and deliverables.

BENEFITS

• Competitive salary and equity package.
• Full health, vision, and dental benefits.
• Opportunities for continuous professional development, including training and conference participation.

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