Multiverse Computing

Multiverse Computing Multiverse is a well-funded and fast-growing deep-tech company founded in 2019. We are the biggest Quantum Software company in the EU. We are also one of the 100 most promising companies in AI in the world (according to CB Insights, 2023) with 150+ employees and growing, fully multicultural and international.

We provide hyper-efficient software to companies seeking to gain an edge with quantum computing and artificial intelligence. Our main products, Singularity and CompactifAI, address critical needs across various industries. Singularity remains a trusted solution for blue-chip companies in finance, energy, manufacturing, cybersecurity, and more. CompactifAI, on the other hand, is a groundbreaking compressing tool of foundational models that uses Tensor Networks to extremely compress AI systems, such as large language models, making these efficient and portable.

You will be working alongside world leading experts to build solutions that tackle real life issues. We look for passionate people that want to grow in an ethics driven environment, promoting sustainability and diversity. We aim to continue building our truly inclusive culture - come and join us.

We are seeking a skilled and experienced Machine Learning Engineer with a strong background in Large Language Models to join our team. You will have the opportunity to work on challenging projects, contribute to cutting-edge research, and shape the future of LLM and NLP technologies. Tackle high value open problems from industry. Collaborate with quantum experts to design and implement new machine learning models.

Required Qualifications

· Degree, Master's or Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, Data Science, or related fields.

· 1+ years of hands-on experience with deep learning models and Industry experience (ideally at Amazon or in a startup).

· Strong background and hands-on experience with different ML technologies, especially natural language processing and large language models.

· Proven experience with Yolo, Llama, Claude, Mistral, or Falcon is a huge plus.

· Excellent problem-solving, debugging, performance analysis, test design, and documentation skills.

· Strong understanding with the fundamentals of GPU architectures.

· Excellent programming skills in Python and experience with relevant libraries (PyTorch, HuggingFace, etc.).

· Experience with cloud platforms (ideally AWS), containerization technologies (Docker) and with deploying AI solutions in a cloud environment

· Excellent written and verbal communication skills, with the ability to work collaboratively in a fast-paced team environment and communicate complex ideas effectively.

· Previous research publications in deep learning is a plus.

· Fluent in English.

Preferred Qualifications

· Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields Research experience in the field of LLMs.

· Expertise in unsupervised machine learning time series.

· Experience training and deploying deep learning models on the Cloud

· Ability to work independently and hit the ground running.

Perks & Benefits

• Indefinite contract.
  
• Equal pay guaranteed.
  
• Variable performance bonus.
  
• Signing bonus.
  
• We offer work visa sponsorship (If applicable).
  
• Relocation package (if applicable).
  
• Private health insurance.
  
• Eligibility for educational budget according to internal policy.
  
• Hybrid opportunity.
  
• Flexible working hours.
  
• Language classes and discounted lunch options
  
• Working in a high paced environment, working on cutting edge technologies.
  
• Career plan. Opportunity to learn and teach.
  
• Progressive Company. Happy people culture

As an equal opportunity employer, Multiverse Computing is committed to building an inclusive workplace. The company welcomes people from all different backgrounds, including age, citizenship, ethnic and racial origins, gender identities, individuals with disabilities, marital status, religions and ideologies, and sexual orientations to apply.