обновлено 6 дней назад
Senior Machine Learning Engineer (LLMs - Agentic Workflows)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Machine Learning Engineer (LLMs - Agentic Workflows) (LLMs and agentic AI): Building and deploying production-grade autonomous agents that plan tasks, use tools, maintain memory, and self-correct with an accent on multi-agent architectures, tool-calling, state management, and safety guardrails. Focus on designing trajectory evaluation frameworks, integrating external systems and vector databases, and monitoring complex workflows with human-in-the-loop checkpoints.
Location: Latin America; fully remote
Company
helps U.S. companies build and scale AI, machine learning, and data teams with talent from Latin America.
What you will do
- Architect agent workflows that decompose complex requests into actionable subtasks.
- Develop Plan-and-Execute and ReAct patterns for planning, tool use, and autonomous execution.
- Design short-term memory, state management, error handling, and self-correction for long-running tasks.
- Build interfaces between LLMs and external software, databases, APIs, legacy systems, and sandboxed Python environments.
- Create evaluation frameworks and monitoring for trajectory success, efficiency, safety, and workflow failures.
- Implement guardrails and human-in-the-loop checkpoints for high-stakes decisions.
Requirements
- 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.
- Strong software engineering fundamentals, including algorithms, system design, OOP, and API integration.
- Experience with agentic architectures, including multi-agent workflows, tool-calling, state management, and human-in-the-loop patterns.
- Experience integrating LangChain, LangGraph, OpenAI, and Claude into production applications, plus expertise in LLM fundamentals and prompt engineering.
- Experience with LangSmith or Arize Phoenix, vector databases for RAG and long-term memory, and AWS, GCP, or Azure.
Culture & Benefits
- Equity participation and a company-wide winter break.
- Annual company retreat and optional in-person events and meetups.
- Education bonus, paid time off, and tailored career roadmaps.
- Transparent, collaborative, learning-focused, and high-performance work environment.
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