Staff Software Engineer - ML Observability

About the role

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence.

Responsibilities

- Drive design and implementation of LLM observability features. - Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems. - Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit. - Develop and extend tools for tracing, evaluating, and debugging LLMs. - Influence architecture decisions and mentor engineers to build resilient, high-performance systems. - Stay close to customer pain points and use those insights to guide product and engineering priorities. - Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team.

Qualifications

- You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience. - Deep understanding of distributed systems and scalable backend architectures. - Hands-on experience building and shipping LLM-powered or GenAI applications. - Understanding of model internals, inference pipelines, evaluation techniques, and prompt engineering. - Ability to thrive in ambiguous, fast-changing spaces and have a product-oriented mindset. - You're excited to shape the next generation of AI observability tools from the ground up. - Communicate clearly, think rigorously, and take pride in clean, maintainable code. - Experience with observability tools/platforms.