Machine Learning Engineer - Large Language Models

Role Overview

This position is for a Machine Learning Engineer specializing in Large Language Models (LLMs), based in Ireland. The role involves joining a dynamic, collaborative environment focused on pioneering AI-driven healthcare solutions. The successful candidate will be responsible for developing, optimizing, and deploying advanced LLMs that drive impactful applications in healthcare and life sciences. This opportunity allows for technical growth and contribution to meaningful AI projects by working alongside cross-disciplinary experts in machine learning, software development, and scientific research.

Key Responsibilities

• Refine and enhance Large Language Models using various fine-tuning methods like Supervised Fine-Tuning (SFT), Parameter-Efficient Fine-Tuning (PEFT), Direct Preference Optimization (DPO), and Proximal Policy Optimization (PPO) tailored for healthcare and life sciences domains.
• Build and improve Retrieval-Augmented Generation (RAG) systems to increase the precision, relevance, and efficiency of AI-enabled information retrieval.
• Gather, clean, and curate quality datasets essential for model training, validation, and ongoing improvements.
• Prepare and optimize AI models for deployment across diverse production environments with emphasis on scalability and operational performance.
• Collaborate with multidisciplinary teams to architect, test, and implement robust deep learning solutions addressing complex healthcare problems.
• Keep abreast of the latest advances in LLMs, ML infrastructure, and AI engineering to continually enhance model accuracy and system dependability.

Candidate Requirements

• Minimum of 5 years’ experience in software engineering and deep learning with production-level deployments.
• Educational background in Computer Science, Data Science, Machine Learning, or closely related field; advanced degrees (Master's or Ph.D.) are preferred.
• Demonstrated expertise in Large Language Model operations, including fine-tuning and optimization techniques.
• Practical experience with frameworks such as Axolotl and a strong understanding of Transformer architectures.
• Proficient with machine learning frameworks, especially PyTorch.
• Knowledge of model serving platforms like vLLM, Text Generation Inference (TGI), and llama.cpp.
• Understanding of model quantization and optimization strategies for constrained environments.
• Excellent analytical, teamwork, and communication skills suited for distributed remote teams.
• Strong enthusiasm for AI innovation and real-world ML application impacts.

Benefits and Work Environment

• Work fully remotely while collaborating internationally.
• Receive a competitive remuneration package.
• Engage with cutting-edge AI and Large Language Model technologies.
• Access continuous learning and professional growth opportunities.
• Contribute to projects with significant impact in healthcare, life sciences, and open-source AI communities.
• Join an inclusive and diverse team committed to equal opportunities and fair hiring.

Additional Information

This recruitment process is managed by a partner company handling applications and next steps. The application is carefully reviewed through an AI-assisted system to ensure unbiased matching with role requirements. Final selections and interviews are conducted by the internal team of the hiring company.

Data privacy and candidate rights are respected in accordance with GDPR and relevant laws. AI tools assist in evaluating applications but do not replace human decision-making in hiring.