Ingeniero de Machine Learning Sénior (LLM)

Required 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 with designing, training or fine-tuning deep learning models, preferably working with transformer or computer vision models.

• 5+ 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.

• Fluent in English

• Previous research publications in deep learning or any tech field is a plus

• 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.

• 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

• CompactifAI is a groundbreaking compression tool for foundational AI models based on Tensor Networks. It enables the compression of large AI systems-such as language models-to make them significantly more efficient and portable.

• Singularity is a quantum- and quantum-inspired optimization platform used by blue-chip companies to solve complex problems in finance, energy, manufacturing, and beyond. It integrates seamlessly with existing systems and delivers immediate performance gains on classical and quantum hardware.

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.

• 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.