The opportunity
As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and…
What you'll do
Design and implement end-to-end agent systems that combine LLM reasoning,: tool use, memory, and control logic to solve recurring enterprise use cases.
Build scalable, reliable agent architectures that can be deployed across many: customers with varying data, tools, and constraints.
Develop evaluation frameworks, datasets, environments, and metrics to measure: agent performance, reliability, and business impact in production settings.
Collaborate closely with product managers, customers, data annotators, and: other engineering teams to translate enterprise requirements into robust agent designs.
Productionize frontier agent techniques (e.g., planning, multi-step reasoning: and tool-use, multi-agent patterns) into maintainable, observable systems.
Own deployment, monitoring, and iteration of agent systems, including failure: analysis and continuous improvement based on real-world usage.
What they're looking for
- Contribute to technical direction and architectural decisions for general: agent development best practices and methods, with increasing scope and leadership at the Staff level.
- + years of experience building and deploying machine learning or AI systems: for real-world, production use cases.
- Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s: degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
- Deep understanding of modern LLMs, prompt-, context-, and system-level: optimization, and agentic system design.
