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Required Senior Malware Researcher
The Dream Job
As a Senior Malware Researcher, you will analyze and reverse engineer malware and tooling used by advanced threat actors, particularly those targeting governments and critical infrastructure. You will apply deep expertise in binary and script analysis to uncover capabilities, configurations, and C2 infrastructure for threat actor attribution and mitigations.
Your work will power our malware catalog, strengthen our understanding of threat actors technical capabilities, and directly support the development of next-generation AI-driven "artificial cyber researchers".
Responsibilities
Perform in-depth static and dynamic analysis of malware, implants, loaders, and related tooling used by APTs and other sophisticated adversaries.
Reverse engineer binaries and scripts (e.g., PE, ELF, .NET, PowerShell, JavaScript/VBA) to determine capabilities, execution flow, persistence mechanisms, and evasion techniques.
Extract and document configuration data and C2 information, and map these to campaigns, infrastructure, and threat actors in collaboration with CTI researchers.
Develop and maintain detection and hunting artifacts such as YARA rules, VT LiveHunt queries, CAPA rules, and sandbox behavior signatures.
Work closely with CyberAI researchers on the development of next-generation artificial cyber researchers and AI-driven analysis capabilities.

Required Senior ML Platform Engineer - Sovereign AI Engineering
The Dream Job
It starts with you - an engineer driven to build the ML platform that turns research into reliable, production-grade intelligence. You care about reproducibility, low-friction experimentation, and infrastructure that earns the trust of the scientists and researchers who depend on it daily. You'll architect and ship our ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - turning models into production capabilities across cloud and on-prem, including air-gapped deployments. A significant part of the platform supports large language models, with unique challenges across training, evaluation, and inference in mission-critical environments.
If you want to make a meaningful impact, join our mission and build the ML platform that drives Sovereign AI products - this role is for you.
Responsibilities
Build and operate ML training infrastructure - distributed training pipelines, compute scheduling, and reproducible experiment workflows that data scientists rely on daily.
Own model serving and inference systems - packaging, deployment, autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models.
Run feature stores, model registries, and dataset versioning - enabling self-serve feature engineering, model lineage, and reproducible experiments across teams.
Build experiment tracking and evaluation infrastructure - automated evals, comparison dashboards, drift detection, and monitoring that give teams visibility into model behavior and performance.
Build and maintain production pipelines for training, fine-tuning workflows, and serving domain models - owning reliability, reproducibility, and scale.
Build and maintain the monitoring and observability layer - model performance tracking, data and prediction drift detection, data quality validation, and alerting.
Improve performance and cost across the ML stack - training throughput, inference latency, batch vs. real-time tradeoffs, and compute cost management.
Ship shared tooling - libraries, templates, CI/CD for models, IaC, and runbooks - while collaborating across Data Platform, AI, Data Science, Engineering, and DevOps. Own architecture, documentation, and operations end-to-end.