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Job Description
About the role
Senior ML Engineer | Early-Stage Cybersecurity Startup
We’re looking for a Senior ML Engineer to join the core engineering team of a well-funded, early-stage Israeli cybersecurity startup building an AI-powered security platform for endpoint environments.
This is a highly hands-on role focused on building the AI layer of a real-time threat detection system — combining LLMs, Machine Learning, AI Agents, and large-scale production systems.
You’ll work on turning complex AI capabilities into reliable, scalable product features, with a strong focus on Production, Cloud, performance, and measurable quality.
What you'll do
Design and build production-grade ML and LLM-powered systems end-to-end
Develop AI Agents that analyze data, detect anomalies, reason over context, and generate security events
Build and optimize data pipelines, retrieval systems, and RAG architectures
Work on Context Engineering, structured outputs, prompt design, and agent workflows
Design robust evaluation frameworks and systematically measure model and system quality
Implement guardrails, monitoring, and observability for non-deterministic AI systems
Make architectural decisions around latency, scale, reliability, and cost
Combine classical algorithms, traditional ML, and LLMs based on the problem at hand
Work closely with a small multidisciplinary team in a fast-moving startup environment
What we’re looking for
5+ years of professional software engineering experience
Strong experience building and operating large-scale production systems
Hands-on experience with Python, Go, Java, or similar languages
Experience building ML or LLM-based systems in Production
Strong understanding of running LLMs under real-world constraints such as scale, latency, reliability, and cost
Hands-on experience with AI Agents, Retrieval, Context Engineering, prompting, and structured outputs
Strong foundation in Data Science, including dataset creation and refinement
Experience designing evaluations and systematically measuring AI system performance
Strong algorithmic foundation and good judgment in choosing between classical algorithms, traditional ML, and LLM-based approaches
Independent, curious, highly hands-on, and comfortable owning complex problems end-to-end
Nice to have
Experience building RAG / Agentic systems
Background in Cybersecurity
Experience working with high-volume or real-time data
Experience taking AI capabilities from experimentation all the way to reliable production features
This is not a pure research role.
We’re looking for a strong engineer who enjoys building real systems, taking ownership, and working at the intersection of Software Engineering, Machine Learning, and AI.