What you'll doDesign and develop new quantum-inspired techniques for compressing Large Language Models, tackling tough use cases across industries
Run rigorous evaluations and benchmarks, then fine-tune and optimise LLMs for accuracy, robustness and efficiency
Build LLM-based applications such as RAG systems and AI agents
Assess model strengths and weaknesses, and propose novel ways to improve performance
Act as a domain expert in LLMs, spotting opportunities for quantum AI-driven innovation
Document your development processes, experiments and results thoroughly
Mentor junior colleagues and share your knowledge to foster a culture of continuous learning
Take part in code reviews and give constructive feedback
Keep up with the latest LLM advances and recommend new tools and technologies
What we're looking forBachelor's, Master's or PhD in AI, Computer Science, Data Science or a related field
Mid-level: 2+ years of hands-on experience with deep learning and neural networks, ideally with LLMs and Transformers
Senior: 5+ years of hands-on experience with deep learning and neural networks, ideally with LLMs and Transformer architectures, or computer vision models
2+ years working with LLM and Transformer models, with excellent command of HuggingFace Transformers, Accelerate, Datasets and similar libraries
Solid mathematical foundations and deep learning expertise across training and inference
Excellent problem-solving, debugging, performance analysis, test design and documentation skills
Strong grasp of GPU architectures and LLM hardware/software infrastructure
Excellent Python skills and experience with PyTorch, HuggingFace and related libraries
Experience with cloud platforms (ideally AWS), Docker, and deploying AI solutions in the cloud
Excellent written and verbal communication, and the ability to collaborate in a fast-paced team
Fluent German
Research publications in deep learning or any technical field are a plus
Responsibilities
What you'll doDesign and develop new quantum-inspired techniques for compressing Large Language Models, tackling tough use cases across industries
Run rigorous evaluations and benchmarks, then fine-tune and optimise LLMs for accuracy, robustness and efficiency
Build LLM-based applications such as RAG systems and AI agents
Assess model strengths and weaknesses, and propose novel ways to improve performance
Act as a domain expert in LLMs, spotting opportunities for quantum AI-driven innovation
Document your development processes, experiments and results thoroughly
Mentor junior colleagues and share your knowledge to foster a culture of continuous learning
Take part in code reviews and give constructive feedback
Keep up with the latest LLM advances and recommend new tools and technologies
What we're looking forBachelor's, Master's or PhD in AI, Computer Science, Data Science or a related field
Mid-level: 2+ years of hands-on experience with deep learning and neural networks, ideally with LLMs and Transformers
Senior: 5+ years of hands-on experience with deep learning and neural networks, ideally with LLMs and Transformer architectures, or computer vision models
2+ years working with LLM and Transformer models, with excellent command of HuggingFace Transformers, Accelerate, Datasets and similar libraries
Solid mathematical foundations and deep learning expertise across training and inference
Excellent problem-solving, debugging, performance analysis, test design and documentation skills
Strong grasp of GPU architectures and LLM hardware/software infrastructure
Excellent Python skills and experience with PyTorch, HuggingFace and related libraries
Experience with cloud platforms (ideally AWS), Docker, and deploying AI solutions in the cloud
Excellent written and verbal communication, and the ability to collaborate in a fast-paced team
Fluent German
Research publications in deep learning or any technical field are a plus
Linked-in
Google