Senior LLM Engineer

Job Overview

We are seeking a skilled and experienced LLM Engineer (Senior and Mid level) with a strong background in Large Language Models to join our team. In this role you will have the opportunity to leverage cutting-edge quantum and AI technologies to lead the design, implementation, and improvement of our language models, as well as working closely with cross-functional teams to integrate these models into our products.

You will have the opportunity to work on challenging projects, contribute to cutting-edge research, and shape the future of LLM and NLP technologies.

As a LLM Engineer, you will:

• Design and develop new techniques to compress Large Language Models based on quantum-inspired technologies to solve challenging use cases in various domains.
• Conduct rigorous evaluations and benchmarks of model performance, identifying areas for improvement, and fine-tuning and optimizing LLMs for enhanced accuracy, robustness, and efficiency.
• Use your expertise to assess the strengths and weaknesses of models, propose enhancements, and develop novel solutions to improve performance and efficiency.
• Act as a domain expert in the field of LLMs, understanding domain-specific problems and identifying opportunities for quantum AI-driven innovation.
• Maintain comprehensive documentation of LLM development processes, experiments, and results.
• Share your knowledge and expertise with the team to foster a culture of continuous learning, guiding junior members of the team in their technical growth and helping them develop their skills in LLM development.
• Participate in code reviews and provide constructive feedback to team members.
• Stay up to date with the latest advancements and emerging trends in LLMs and recommend new tools and technologies as appropriate.

• Master's or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields.
• Mid: 2+ years of hands-on experience with designing, training or fine-tuning transformer models.
• Senior: 5+ years of hands-on experience with designing, training or fine-tuning transformer and other deep learning models (e.g. computer vision).
• 2+ year of hands-on experience using LLM and Transformer models, with excellent command of libraries such as Hugging Face Transformers, Accelerate, Datasets, etc.
• Solid mathematical foundations and theoretical understanding of deep learning algorithms and neural networks, both training and inference.
• 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, Hugging Face, 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.

• Proven experience (4+ years) delivering successful AI-driven projects in an industrial environment.
• Spanish Language skills.
• Experience running large-scale workloads in high-performance computing (HPC) clusters.
• Experience in handling large datasets and ensuring data quality.
• Experience with inference and deployment environments (TensorRT, vLLM, etc.).
• Experience in accuracy evaluation of LLMs (OpenLLM Leader board).
• Experience building and evaluating RAG systems.
• Experience in building non-LLM deep learning applications, e.g., computer vision, audio or signal processing.
• Familiarity with AI ethics and responsible AI practices.
• Experience in Dev Ops/MLOps practices in deep learning product development.

• 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.
• A high-performance, collaborative environment, operating at pace on cutting-edge technologies.
• Career plan. Opportunity to learn and teach.

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.