LLM Engineer

Open worldwide
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Why you can actually get this job

The posting explicitly states 'Worldwide' scope with no geographic, work authorization, language, or timezone restrictions. The target user (anglophone Caribbean resident, English monolingual, UTC-5, no US/UK work auth) satisfies all stated requirements and passes all hard gates. The employment path is employee (full-time, benefits-eligible role), which is compatible with Caribbean hiring.

“Worldwide” Geographic scope — No location restrictions stated — worldwide.
“Worldwide” Geographic scope — Explicit worldwide geographic scope with no country or regional restrictions stated.
“KDCI Outsourcing is looking for an LLM Engineer to design, fine-tune, and deploy large language model solutions that solve real business problems.” Work authorization — No work authorization requirement, visa sponsorship clause, or citizenship mandate anywhere in the posting.
“Employment type as stated: Full Time” Employment path — Employee role (full-time), not contractor; no visa sponsorship phrase present to trigger G1 exclusion.

About the role

Role Summary

KDCI Outsourcing is looking for an LLM Engineer to design, fine-tune, and deploy large language model solutions that solve real business problems. You'll work across the model lifecycle — from prompt and architecture design to evaluation and production monitoring — collaborating with product and engineering teams to ship reliable AI features.

Key Responsibilities

  • Design, fine-tune, and optimize large language models for specific use cases
  • Build and maintain evaluation harnesses to measure model quality and safety
  • Implement RAG (retrieval-augmented generation) pipelines and prompt strategies
  • Monitor model performance in production and iterate on improvements
  • Collaborate with product and engineering teams to integrate LLM features
  • Stay current with emerging LLM research, architectures, and tooling

Requirements

Requirements

  • 3+ years of hands-on experience with large language models and NLP
  • Strong understanding of transformer architectures (GPT, BERT, LLaMA, etc.)
  • Proficiency in Python and ML frameworks such as PyTorch or TensorFlow
  • Experience with fine-tuning, prompt engineering, and hyperparameter optimization
  • Track record of deploying ML/LLM systems in production environments

Nice-to-Haves

  • Experience with vector databases and RAG pipelines
  • Familiarity with model quantization and inference optimization
  • Background in AI safety or content moderation systems

Highlights

  • Build and deploy cutting-edge LLM solutions using AI, RAG, and modern ML frameworks.

Originally posted on Himalayas

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At a glance

  • EmploymentNot stated in posting
  • Hiring scopeOpen worldwide
  • SalaryNot disclosed
  • Posted1mo ago

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