Senior Machine Learning Engineer

10 set - Modena
Factored

Fully remote | Complete engagement job
Founded in Palo Alto by Dr. Andrew Ng and Israel Niezen, Factored helps U.S. companies build and scale world-class AI, ML, and Data teams, powered by the top 1% of LATAM talent, with a defining purpose: To empower brilliant humans, unleash their potential, and amplify their impact in the world.
At Factored, you’ll be part of a community that values learning, ownership, and authenticity, where your growth is personal and your ideas matter. We’re transparent, curious, and collaborative. We strive for excellence, celebrate diversity, encourage curiosity, and build an environment where you can truly thrive.
We are seeking a skilled Senior Machine Learning Engineer to join our team, with a specialized focus on agentic workflows. The ideal candidate will have experience designing, developing, and deploying systems that transition LLMs from passive responders to autonomous agents capable of planning, tool-use, and self-correction.
Functional Responsibilities:




Architect how the agent breaks down a complex user request into a series of actionable sub-tasks.
Develop "Plan-and-Execute" or "ReAct" (Reason + Act) patterns where the model thinks before it acts.
Design robust systems to maintain "short-term memory" across long-running tasks, ensuring the agent doesn't lose track of its goal or get stuck in infinite loops.
Create the interface between the LLM and external software, databases, or APIs.
Standardize how the agent calls functions, interacts with legacy systems, or executes Python code in a sandboxed environment.
Implement error-handling and self-correction.
Build custom evaluation frameworks to measure trajectory success—not just whether the final answer was right, but if the steps taken to get there were efficient and safe.
Set up monitoring to visualize the agent's "thought process" and identify exactly where a multi-step workflow broke down.
Ensure the agent doesn't "hallucinate" tool usage or take unintended actions through st

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