Machine Learning Engineer (LLM)

Job Overview

We are seeking a skilled and experienced Machine Learning Engineer 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 Machine Learning 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 optimising LLMs for enhanced accuracy, robustness, and efficiency.

• Build LLM based applications such as RAG and AI agents.

• 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.

• Design, train and deliver custom deep learning models for our clients

• Work in diverse areas beyond LLM, e.g., computer vision.

• 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.

Required minimum Qualifications:

• Bachelor's, Master's or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields.

• 2+ years of hands-on experience with designing, training or fine-tuning deep learning models, preferably working with transformer or computer vision models.

• 2+ year of hands-on experience using transformer models, with excellent command of libraries such as HuggingFace 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 and and LLM hardware/ software infrastructures.

• 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 or any tech field is a plus

Preferred Qualifications:

• 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 Leaderboard).

• 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 DevOps/MLOps practices in deep learning product development.

Perks and 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