> Markdown version of [/jobs/ext/3901210-mid-senior-ai-llm-engineer](https://www.wearedevelopers.com/jobs/ext/3901210-mid-senior-ai-llm-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Mid/Senior AI LLM Engineer - **Company:** Jobgether - **Location:** Netherlands (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Training Data, AI Evaluation, Artificial Intelligence, Software Debugging, DevOps, Web Development, Python (Programming Language), Machine Learning, Performance Tuning, Strategies of Testing, QLoRA, Pytorch, Large Language Models, HuggingFace, Machine Learning Operations - **Published:** October 24, 2026 - **Apply:** https://www.adzuna.nl/details/5939508476 ## About the Role * Proven hands-on experience fine-tuning open-weight large language models and deploying models into production environments. * Strong Python programming skills, including experience developing, testing, and maintaining machine-learning workflows. * Practical experience with PyTorch and Hugging Face or comparable machine-learning frameworks and model development tools. * Experience with model training and adaptation techniques such as supervised fine-tuning (SFT), Low-Rank Adaptation (LoRA), and Quantized Low-Rank Adaptation (QLoRA). * Familiarity with preference-based training and alignment techniques, such as Direct Preference Optimization (DPO) or Group Relative Policy Optimization (GRPO). * Experience preparing and managing training datasets, improving data quality, and developing evaluation frameworks to assess model behavior and output quality. * Practical experience with GPU-based model training, performance optimization, and debugging training-related technical issues. * Strong analytical and problem-solving skills, with the ability to investigate model behavior, identify root causes, design experiments, and demonstrate measurable improvements. * Understanding of the challenges involved in deploying and maintaining LLM-powered applications, including response quality, consistency, inference performance, and ongoing monitoring. * Experience working on consumer-facing AI products, with an understanding of how model quality and conversational behavior affect user experience. * Comfort working with minimally restricted or uncensored AI models, including explicit adult or NSFW content and sensitive moderation material, while applying appropriate safeguards and content-handling practices. * Ability to work independently in a remote environment, manage experiments effectively, document findings, and collaborate with cross-functional teams. * Strong communication skills, attention to detail, and a continuous-learning mindset, with the ability to translate experimental results into practical product improvements. * Fully remote working arrangement within Europe. * Long-term collaboration opportunities, with B2B contracting preferred. ## Description As a Mid/Senior AI LLM Engineer, you will develop, fine-tune, and optimize self-hosted large language models that power personalized, engaging AI conversations. You will work across the full model development lifecycle, from preparing training datasets and running GPU-based experiments to evaluating performance and deploying improvements into production. Your work will help enhance conversational quality, long-term memory, personality consistency, and multilingual interactions. Collaborating with AI engineers, product specialists, web developers, and DevOps teams, you will turn experimental findings into reliable, scalable solutions. This hands-on role offers the opportunity to work with open-weight models, advanced fine-tuning techniques, and practical AI evaluation frameworks. You will join a remote-first environment focused on building innovative, consumer-facing AI products while continuously improving model performance and user experience. Accountabilities * Fine-tune and optimize existing open-weight large language models to improve conversational quality, response accuracy, consistency, and personalization. * Prepare, curate, and enhance training datasets to support effective model learning, reduce undesirable outputs, and improve the relevance and naturalness of generated responses. * Design and implement evaluation frameworks, benchmarks, and testing methodologies to measure model quality, identify weaknesses, and validate improvements. * Improve conversational memory, personality consistency, and the ability of models to maintain coherent, context-aware interactions over extended conversations. * Develop multilingual conversational capabilities and support interactions involving multiple characters, ensuring natural and consistent behavior across different scenarios. * Investigate model failures and performance limitations, adjusting training data, prompts, model configurations, and response filters to address identified issues. * Conduct GPU-based training and fine-tuning experiments, troubleshoot infrastructure and performance issues, and optimize training workflows for efficiency and reliability. * Apply modern model adaptation and alignment techniques, including supervised fine-tuning, LoRA, QLoRA, and preference-based optimization methods where appropriate. * Deploy improved models into production environments, monitor their performance, analyze user-facing outcomes, and implement iterative refinements based on evaluation results. * Collaborate with AI engineering, product, web development, and DevOps teams to integrate model improvements into consumer-facing applications and align technical work with product objectives. * Work with sensitive conversational use cases and moderation requirements, balancing model behavior, user experience, and applicable content policies.