Senior Applied ML Research Engineer, Agentic Security
Designs threat models and experiments for agentic AI security risks, builds prototypes with fine-tuned models and analysis tools, and turns research into scalable product defenses. Requires MS/PhD in CS/ML, production coding skills, and security mindset.
Salary not listed
RemoteML Engineering
About the role
Responsibilities
Define and validate threat models for agentic systems, identifying which tool characteristics must co-exist to enable data exfiltration and malicious state change, and how to break those combinations
Design and run experiments: create synthetic environments like file systems and tools, create task distributions that have attack paths and apply different attack strategies
Break (manually and using optimization algorithms such as RL) agentic systems
Design and improve static and dynamic analysis methods that automatically map tool capabilities to risk across diverse tool ecosystems, and make those methods scale
Turn research insights into product-facing capabilities: risk classification, automated guardrail generation, and quantitative threat measurement
Build measurement tools: eval harnesses, monitoring, dashboards, and feedback loops that quantify security outcomes
Build capability and regression evals
Optimize systems for real-world constraints (latency, cost, reliability) without losing scientific rigor
Requirements
MS or PhD in CS/ML (or equivalent research experience) and enjoy working under uncertainty
Fine-tuned and evaluated models in practice and can reason about data quality, overfitting, evals, and deployment constraints
Write strong production code, comfortable owning the infrastructure that makes agentic evals run end-to-end; care about reproducibility and instrumentation
Motivated by security problems and enjoy thinking like both builder and attacker
Reason about how capabilities combine into risk: not just individual vulnerabilities, but system-level attack surfaces across tool ecosystems
Communicate clearly, iterate fast, and can hold a technical narrative from "hypothesis" to "shipped"
Compensation & Benefits
Competitive salary + equity
Remote-friendly, with preference for candidates based in Amsterdam, Paris, Poland, New York, or San Francisco
Fully funded team retreats every 8 weeks
Health insurance allowance for you and your dependents
Wellbeing, learning, and home office allowances
Skills
Machine LearningFine-TuningReinforcement LearningStatic AnalysisDynamic AnalysisPythonEvaluation FrameworksDashboardsMonitoringAgentic Systems
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