Job OverviewArtemis 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.
A core part of this effort is using
agents as the primary classification and reasoning layer across our platform - enabling us to move beyond static rules and traditional approaches to understand and act on complex security data.
This is a high-impact role with significant ownership. You'll work across critical parts of the system - from LLM-powered classification and detection to large-scale data and analytics infrastructure - depending on your strengths and the problems at hand.
You will help define architecture, make key technical decisions, and drive projects from concept through production. This role is for engineers who are comfortable operating in ambiguity, care deeply about quality, and want to build intelligent systems that matter.
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. You're not boxed into a single layer.
- 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 - 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.
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
- Experience building large scale detection systems that combine heuristics, traditional ML techniques, and generative AI
- Experience building AI agents for security operations use cases
CompensationWe offer a competitive compensation of 180,000$- 250,000$ per year, and a top-of-market equity component. A variety of factors are considered when determining the compensation, including a candidate's professional experience. Final offer amounts may vary from the amounts listed.
