AI/ML Engineer

Artemis is building the future of AI-driven defense - helping companies detect and defend themselves effectively in an era where AI is fighting AI on the cyber battlefield.

We’re backed by First Round Capital, Brightmind, and a group of the cybersecurity industry’s most prominent Operators.

Our founders, Shachar (ex-Palo Alto Networks, AWS, Demisto) and Dan (ex-Abnormal Security, Twitter) have previously built, launched, and scaled cybersecurity products loved and trusted by tens of thousands of customers, and have the customer, technology, and security know-hows to deliver this vision.

Our exceptionally strong team includes software engineers, AI researchers, security engineers, and product designers hailing from Google, Abnormal AI, Wiz, Meta, AWS, CERN, SentinelOne, and more.

We are growing our team and looking for passionate builders to join us and support our expanding customer base.

Artemis ingests and analyzes exabytes of streaming data from cloud platforms, identity providers, network logs, and more. We’re building a new, large-scale, AI-native data platform from the ground up – and we’re looking for exceptional AI/ML Engineers to help shape and build it. You’ll work alongside engineers who architected some of the world’s biggest distributed systems.

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  Own and deliver major ML-driven initiatives – Design, build, and ship end-to-end features and systems that use LLMs to power Artemis’ detection, classification, and analytics.

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  Build and scale LLM-powered systems – Work on services and pipelines that apply LLMs to ingest, process, and classify massive volumes of security telemetry with high reliability and performance.

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  Contribute across the stack – Depending on the problem, this may include LLM pipelines, backend services, APIs, data infrastructure, or user-facing applications. You’re not boxed into a single layer.

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  Make architectural decisions – Evaluate trade-offs across prompting vs fine-tuning, model selection, retrieval strategies, and system design to ensure scalability, accuracy, and cost-efficiency.

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  Bring strong engineering and ML judgment – Balance speed and quality, know when to iterate and when to invest, and raise the bar for model performance, system design, and operational excellence.

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  Collaborate deeply – Work closely with product, design, security, and platform teams to turn complex problems into reliable, LLM-driven solutions.

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  Leverage AI-native development practices – We actively use AI tools to increase velocity and quality. You’ll be expected to embrace and evolve how we build and deploy LLM-powered systems in an AI-first environment.

• Experience training, deploying, and monitoring ML models from scratch (without relying on extensive existing infrastructure)

• Experience optimizing generative AI systems, including developing metrics, building validation sets, and working with domain experts

• Able to build statistical models from scratch and justify them mathematically

• Strong intuition for feature engineering tradeoffs spanning code, systems, and model performance

• Ability to spot and debug model degradations in production applications

• Strong intuition for how to represent complex structured data to an LLM

• Experience building models for time series data and corporate telemetry data

• Experience building large scale detection systems that combine heuristics, traditional ML techniques, and generative AI

• Experience building AI agents for security operations use cases