Senior Machine Learning Engineer

Job Overview

We are seeking a skilled and experienced Senior 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.

Responsibilities

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.

Required Qualifications

Master's or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields.
5+ years of hands-on experience with deep learning models and neural networks working with Large Language Models or computer vision models, preferably with experience in Transformers.
Solid mathematical foundations and expertise in deep learning algorithms and neural networks, both training and inference.
Excellent problem-solving, debugging, performance analysis, test design, and documentation skills.
Strong understanding of 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 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 Spanish and English.

Preferred Qualifications

Proven experience (4+ years) delivering successful AI-driven projects in an industrial environment.
Experience running large-scale workloads in high-performance computing (HPC) clusters.
Experience in DevOps/MLOps practices in deep learning product development.
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.
Familiarity with AI ethics and responsible AI practices.