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Factored

Senior Machine Learning Engineer (LLMs - Agentic Workflows)

RemoteLATAM+United States
Published
Role
AI / ML
Experience
Senior
Salary not disclosed
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Open to Anywhere in LATAM + US. Set where you work from to check your eligibility.

No BS summary

Senior ML engineer in Latin America with 5+ years building and deploying production ML. Needs hands-on agentic LLM workflows, LangChain/LangGraph/OpenAI/Claude, RAG/vector databases, cloud deployment, and strong software engineering fundamentals.

Core skills

RAGLLMsAgentic workflows

Required skills

Machine LearningOOPAPI designAPI integrationLangChain/LangGraph/OpenAI/ClaudePrompt engineeringLangSmith/Arize PhoenixPinecone/Milvus/QdrantAWS/GCP/Azure

What you'll do

  • 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 strict guardrails and Human-in-the-Loop (HITL) checkpoints for high-stakes decisions.

What they require

  • Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
  • 5+ years of hands-on experience developing and deploying machine learning models in production environments.
  • Strong software engineering fundamentals, including data structures, algorithms, system design, OOP, and API design & integration.
  • Proven experience designing and implementing agentic architectures, including multi-agent workflows, tool-calling, state management, and human-in-the-loop patterns.
  • Expertise in integrating Generative AI frameworks and APIs (such as LangChain, LangGraph, OpenAI, and Claude) into production-grade applications.
  • Strong understanding of LLM fundamentals, systematic prompt engineering (chain-of-thought, few-shot), and debugging tools like LangSmith or Arize Phoenix.
  • Experience with vector databases (Pinecone, Milvus, Qdrant) for retrieval-augmented generation (RAG) and long-term agent memory.
  • Experience with cloud platforms such as AWS, GCP, or Azure for deploying AI workloads.

Benefits

  • Ownership through equity participation.
  • Annual company retreat.
  • Education bonus for continuous learning.
  • Company-wide winter break.
  • Paid time off.
  • Optional in-person events and meetups.
  • Tailored career roadmaps.
  • High-performance culture.
  • Freedom to do the best work of their lives while learning and growing as much as possible.
  • Career and professional growth support.
  • Transparent workplace, where EVERYBODY has a voice in building OUR company.
  • Learning and growth are available to everyone based on their merits.

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.

🇺🇸 United StatesAI

Details

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Salary not disclosed