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Multiverse Computing is a well-funded, fast-growing deep-tech company founded in 2019, recognized by CB Insights as one of the 100 most promising AI companies globally. With 180+ employees, the company is the largest quantum software company in the EU, delivering hyper-efficient software for quantum computing and AI applications.
You will join a multicultural, international team to design, implement, and improve large language models using cutting-edge quantum and AI technologies. This role offers the opportunity to work on challenging projects that tackle real-world problems across finance, energy, manufacturing, and other industries.
Key Responsibilities:
- Design and develop novel techniques to compress Large Language Models using quantum-inspired technologies
- Conduct rigorous evaluations and benchmarks of model performance, identifying improvement areas and fine-tuning LLMs for accuracy, robustness, and efficiency
- Build LLM-based applications such as RAG systems and AI agents
- Assess model strengths and weaknesses, propose enhancements, and develop solutions to improve performance
- Act as a domain expert in LLMs, identifying opportunities for quantum AI-driven innovation
- Design, train, and deliver custom deep learning models for clients
- Work in diverse areas including computer vision and other deep learning domains
- Maintain comprehensive documentation of development processes, experiments, and results
- Mentor junior team members, fostering a culture of continuous learning
- Participate in code reviews and provide constructive feedback
- Stay current with latest advancements in LLMs and recommend new tools and technologies
The company offers hybrid flexibility, indefinite contracts, equal pay, performance bonuses, signing bonuses, work visa sponsorship, relocation packages, private health insurance, educational budgets, flexible working hours, and language classes.
REQUIREMENTS:
Minimum Qualifications:
- Bachelor's, Master's, or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields
- 5+ years of hands-on experience designing, training, or fine-tuning deep learning models, preferably with transformer or computer vision models
- 5+ years of hands-on experience using transformer models with excellent command of HuggingFace Transformers, Accelerate, Datasets, and related libraries
- Solid mathematical foundations and theoretical understanding of deep learning algorithms and neural networks (training and inference)
- Excellent problem-solving, debugging, performance analysis, test design, and documentation skills
- Strong understanding of GPU architectures and LLM hardware/software infrastructures
- Excellent Python programming skills with experience in PyTorch, HuggingFace, and related libraries
- Experience with cloud platforms (ideally AWS), containerization (Docker), and deploying AI solutions in cloud environments
- Excellent written and verbal communication skills with ability to work collaboratively in fast-paced teams
- Fluent in English
- Previous research publications in deep learning or tech fields is a plus
Preferred Qualifications:
- Experience running large-scale workloads in high-performance computing (HPC) clusters
- Experience handling large datasets and ensuring data quality
- Experience with inference and deployment environments (TensorRT, vLLM)
- Experience in accuracy evaluation of LLMs (OpenLLM Leaderboard)
- Experience building and evaluating RAG systems
- Experience building non-LLM deep learning applications (computer vision, audio, signal processing)
- Familiarity with AI ethics and responsible AI practices
- Experience in DevOps/MLOps practices in deep learning product development
