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Senior Machine Learning Engineer (RAGs)

1 month, 1 week ago
Latin America
Full-time
Senior
Machine Learning Engineer
Software Development
AWS Deep Learning GCP Generative AI GPT Machine Learning Python PyTorch TensorFlow
Apply Now
Factored

Factored

Factored AI provides top AI engineers and solutions for businesses, specializing in business analytics and data science to drive innovation and success.

Internet Software & Services
51-250
Founded 2019
View All Jobs 9

Description

  • Design, develop, optimize, and fine-tune RAG models for real-world client problems.
  • Improve RAG performance through advanced algorithms, prompting, and model fine-tuning.
  • Collaborate with client data, engineering, and leadership teams to identify AI/ML opportunities and build infrastructure.
  • Adapt large language models for specific tasks and domains within RAG systems.
  • Deploy RAG models into production and ensure reliable integration and long-term performance.
  • Develop GenAI product frameworks, including search interfaces, chatbots, and summarization tools.
  • Write clean, maintainable, scalable, documented, and testable production code.
  • Provide technical leadership on AI/ML solution design and evaluation.
  • Prioritize customer needs and user experience throughout product development.

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 production machine learning models.
  • 4+ years of experience with production NLP and deep learning models using PyTorch and TensorFlow.
  • At least 1 year of experience with RAG and advanced model optimization techniques.
  • Strong Python and production-level software development skills.
  • Expertise with LLMs such as GPT, Gemini, and Claude.
  • Experience with LLM frameworks such as LangChain.
  • Strong understanding of prompting techniques and prompting versus fine-tuning trade-offs.
  • Experience with AWS, GCP, or equivalent on-premise platforms; AWS preferred.

Benefits

  • Fully remote work arrangement.
  • Equity participation.
  • Annual company retreat and optional in-person events.
  • Education bonus for continuous learning.
  • Company-wide winter break and paid time off.
  • Tailored career roadmaps and professional growth support.

Interested in this position?

Apply directly on the company website

Apply Now

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