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RMG Talent

External role

Mid/Senior AI LLM Engineer – Remote (Europe) at RMG Talent, via carbon.talent

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Listed from the company's careers page

via Himalayas

Remote · United StatesFull-time

Stack

AI-EngineerLLM-EngineerMachine-Learning-EngineerGenerative-AI-EngineerSenior-AI-LLM-EngineerSenior-LLM-Engineer

Must-haves

  • Hands-on experience fine-tuning open-weight language models and deploying them into production
  • Strong Python skills
  • Practical experience with PyTorch and Hugging Face
  • Experience with supervised fine-tuning and LoRA/QLoRA
  • Familiarity with preference-based training methods such as DPO or GRPO
  • Practical GPU training and debugging experience

About this role

This is a remote position.

About the role We are looking for a hands-on Mid/Senior AI LLM Engineer to improve the self-hosted large language models that power consumer-facing conversational AI products. The role centres on fine-tuning open-weight LLMs, building datasets and evaluations, debugging GPU training runs and taking measurable improvements into production. This is a specialist post-training engineering position: you will own the full loop from data and training to evaluation and deployment. It is not an AI research role, nor a role connecting to third-party chatbot APIs. Key responsibilities
  • Fine-tune and post-train open-weight language models and deploy them into production
  • Build training datasets and evaluate model performance independently
  • Work on long-context consistency, personalization, multilingual quality, group chat and better model evaluation
  • Debug and optimise GPU training workloads
  • Measure and ship improvements for consumer-facing conversational AI products
  • Contribute to ongoing moderation and safety evaluations
Location and terms: Fully remote within Europe. Start: ASAP. Salary: EUR 80,000–120,000 gross per year. Long-term collaboration, with B2B contracting preferred.

Requirements

  • Hands-on experience fine-tuning open-weight language models and deploying them into production
  • Strong Python skills
  • Practical experience with PyTorch and Hugging Face
  • Experience with supervised fine-tuning and LoRA/QLoRA
  • Familiarity with preference-based training methods such as DPO or GRPO
  • Practical GPU training and debugging experience
  • Ability to build training datasets and evaluate model performance independently
  • Experience working on consumer-facing AI products
  • Comfortable working with unrestricted AI models and adult content as part of the product, including sensitive moderation material
  • A hands-on engineering profile - not an AI researcher and not a developer who simply connects to ChatGPT APIs

Benefits

  • Fully remote working within Europe
  • Long-term collaboration, with B2B contracting preferred
  • 20 working days of paid leave
  • $100 monthly health insurance allowance
  • Equipment budget
  • Access to AI development tools
  • Learning and development support
  • Annual team gathering
  • Opportunity to work on self-hosted LLMs powering consumer-facing AI products

Originally posted on Himalayas