Delphos

Security Engineer

• Source and prepare diverse compiled‑software datasets; own ingestion, labeling, and quality (metadata, reproducibility, version control).
• Research and automate firmware extraction, unpacking, and structural analysis for higher‑precision workflows.
• Build vulnerability feed automation; link code changes to known CVEs and surface prioritized fixes.
• Translate vulnerability & behavior insights into training/evaluation datasets; review model outputs to refine curation, quality, and interpretability.
• Prototype AI‑assisted RE workflows (function labeling, behavior clustering, automated triage, summarization).
• Explore how generative models augment reverse engineering, static/dynamic analysis, and vulnerability discovery.
• Integrate research into production systems; evolve shared infrastructure for dataset management, reproducibility, and continuous evaluation.
• Support internal tooling and code health that streamlines collaboration across security, engineering, and AI.
• Enable AI to reason about compiled software at scale, improving detection accuracy, explainability, and product readiness.
• Contribute to the broader research community through benchmarking, responsible disclosure, and publications.

Security Researcher, Software Engineer

Platform Engineer

• Build robust systems for data storage, retrieval, and processing, all within our monorepo environment.
• Own the reliability and observability stack that keeps our ML and analysis pipelines fast, secure, and reliable.
• Optimize cloud infrastructure for cost efficiency, scalability, and performance across storage, compute, and networking layers.
• Build monitoring systems that balance performance and stability under mission-critical workloads.
• Collaborate with Security Engineers to enforce best practices for data isolation, access control, and auditability.
• Support compliance alignment for RMF, SOC 2, and on-prem deployments without slowing down iteration speed and engineering agility.
• Remove friction, speed up iteration, and reduce cognitive load for other engineers by simplifying local development, automating the boring stuff, adding tools to solve pain points, and communicating best practices to the rest of the company.
• Help own code health throughout the company and engage proactively in efforts to regularly improve the codebase as a whole.
• Design and manage end-to-end ML pipelines, from dataset ingestion and preprocessing to model training, validation, and deployment, ensuring the deployment of scalable and high-performance models.
• Partner with AI and Security Research teams to ensure that model artifacts are versioned, reproducible, and production-ready.
• Work closely with engineers to maintain the infrastructure that seamlessly integrates data feeds and manages the flow of meticulously labeled datasets across internal systems.

Security Researcher, Software Engineer

Platform Engineer – Infrastructure