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About the Role

This opportunity is offered on behalf of a partner company located in Germany, specializing in innovative AI-driven healthcare solutions. The successful candidate will join a dynamic, collaborative environment dedicated to developing advanced Large Language Models (LLMs) that address real-world challenges in healthcare and life sciences. You will play a key role in designing, improving, and deploying LLMs while working alongside professionals from machine learning, software development, and scientific communities to create impactful AI applications.

Key Responsibilities

Apply advanced fine-tuning and optimization methods such as Supervised Fine-Tuning (SFT), Parameter-Efficient Fine-Tuning (PEFT), Direct Preference Optimization (DPO), and Proximal Policy Optimization (PPO) to enhance Large Language Models tailored for healthcare and life science contexts.
Build and refine Retrieval-Augmented Generation (RAG) systems to boost the precision, relevance, and efficiency of AI-based information retrieval.
Gather, preprocess, clean, and maintain high-quality datasets to undergird training and evaluation cycles for machine learning models.
Transform, optimize, and package AI models for production deployment across varied serving environments, ensuring scalability and top performance.
Collaborate with multidisciplinary teams to design, test, and implement robust deep learning solutions that solve sophisticated healthcare problems.
Continuously monitor and integrate the latest breakthroughs in LLMs, machine learning infrastructure, and AI engineering standards to enhance the models' effectiveness and robustness.

Candidate Requirements

A minimum of 5 years of professional experience in building production-ready software engineering and deep learning solutions.
A formal degree in Computer Science, Data Science, Machine Learning, or a related technical discipline; a Master's or Ph.D. qualification is highly preferred.
Demonstrable experience with Large Language Models encompassing fine-tuning and optimization methodologies.
Hands-on proficiency with frameworks such as Axolotl and profound understanding of Transformer architectures.
Solid experience with machine learning frameworks, especially PyTorch.
Knowledge of model serving technologies including vLLM, Text Generation Inference (TGI), and llama.cpp.
Familiarity with techniques of model quantization and performance tuning for deployment in resource-limited environments.
Strong analytical thinking, teamwork, and communication abilities suited for effective collaboration within distributed teams.
A deep passion for AI innovation and the application of machine learning to meaningful, real-world impacts.

Benefits and Perks

Enjoy a fully remote working arrangement collaborating with an international, diverse team.
Receive a competitive salary package reflective of your skills and experience.
Participate in pioneering AI research and development related to Large Language Models.
Access ongoing opportunities for professional growth and learning.
Contribute to impactful projects spanning healthcare, life sciences, and open-source AI initiatives.
Work within an inclusive and equitable environment dedicated to diverse hiring practices.

Additional Information

This position is managed through an AI-assisted candidate screening system that ensures fair, objective consideration based on core qualifications. Subsequent interview and selection stages are conducted directly by the employer. The application process observes stringent data privacy standards in accordance with GDPR. AI tools may assist in certain recruitment tasks; however, all final decisions are made by human recruiters.

Machine Learning Engineer - Large Language Models