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. Backed by First Round Capital, Brightmind, and a group of the cybersecurity industry’s most prominent operators, our founders (ex-Palo Alto Networks, AWS, Demisto, Abnormal Security, Twitter) have previously built, launched, and scaled cybersecurity products trusted by tens of thousands of customers. Our team includes engineers, AI researchers, and designers from Google, Abnormal AI, Wiz, Meta, AWS, CERN, SentinelOne, and more.

About the role

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 are looking for exceptional AI/ML Engineers to help shape it. You’ll work alongside engineers who architected some of the world’s biggest distributed systems, using agents as the primary classification and reasoning layer across our platform. This high-impact role offers significant ownership, spanning LLM-powered classification, detection, and large-scale data infrastructure.

Responsibilities

• 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.
• 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.
• Contribute across the stack—depending on the problem, this may include LLM pipelines, backend services, APIs, data infrastructure, or user-facing applications.
• 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.
• 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.
• Collaborate deeply—work closely with product, design, security, and platform teams to turn complex problems into reliable, LLM-driven solutions.
• Leverage AI-native development practices—embrace and evolve how we build and deploy LLM-powered systems in an AI-first environment.

Qualifications

• 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.
• Bonus: Experience building models for time series data and corporate telemetry data.
• Bonus: Experience building large-scale detection systems that combine heuristics, traditional ML techniques, and generative AI.
• Bonus: Experience building AI agents for security operations use cases.

Benefits

• Make a real-world impact by empowering cybersecurity teams to defend against advanced threats.
• Work with some of the smartest and most driven people in the industry—guaranteed to learn more in one year than in ten elsewhere.
• Push the boundaries of technology by building cutting-edge AI capabilities in cybersecurity.
• Innovative culture with a focus on customer obsession, high-quality execution, open communication, mentorship, and learning.
• Autonomy to drive projects and support to grow professionally.

Pay

Competitive compensation of $180,000–$250,000 per year, plus top-of-market equity. Final offer amounts may vary based on professional experience.