Senior Machine Learning Engineer – LLMs, Agentic Workflows
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Job Description
Senior Machine Learning Engineer designing autonomous agents and multi-agent workflows for Factored. Building production AI systems that help U.S. companies scale teams with LATAM talent.
Responsibilities:
- Architect agent task decomposition into actionable sub-tasks
- Develop Plan-and-Execute and ReAct patterns
- Design short-term memory systems for long-running tasks
- Create interfaces between LLMs and external software, databases, and APIs
- Standardize function calling, legacy-system interaction, and sandboxed Python execution
- Implement error handling and self-correction
- Build evaluation frameworks measuring trajectory success, efficiency, and safety
- Set up monitoring to visualize agent processes and diagnose workflow failures
- Implement guardrails and Human-in-the-Loop checkpoints for high-stakes decisions
- Own intelligent automation systems end-to-end from prototyping through production deployment
Requirements:
- 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 such as Pinecone, Milvus, and 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
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